Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Friday, 12 November 2021
Monday, 20 September 2021
Indian Currency Recognition Using Deep Learning Convolutional Neural Network CNN Python Project With Source Code | IEEE Based Projects
ABSTRACT
The appearance of the currency is part of this development and it is affected directly, where there is exploited in incorrect form by copying the currency in a manner similar to the reality. Therefore, it became necessary to implement a proposal for being a suitable as solution not inconsistent with the different cultures, time and place. This clear through add the watermarks inside currency, which is difficult to be copied. At the same time, this watermarks may be visible to the naked eye so can easily inferred or it is invisible. However the high resolution imaging devices can copy these additions. In this research, we have proposed a system to distinguish the currencies by the program that working a submission inferred to the watermark by feature extraction determined the type of currency. In addition to, it determined category of the currency. Benefit of it, is reducing as much as possible the spread of counterfeit currency and this system can be used by any user wants to make sure of the currency.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com
Early Stage Leukemia Blood Cancer Detection Using Matlab Source Code | IEEE Based Projects
ABSTRACT
Leukemia Blood cancer is the most prevalent and it is very much dangerous among all type of cancers. Early detection of blood cancer has the potential to reduce mortality and morbidity. There are many diagnostic technologies and tests to diagnose blood cancer. However many of these tests are extremely complex and subjective and depend heavily on the experience of the technician. To obviate these problems, image processing techniques is use in this study as promising modalities for detection of Leukemia blood cancer. The accuracy rate of the diagnosis of blood cancer by using image processing will be yield a slightly higher rate of accuracy then other traditional methods and will reduce the effort and time. We first discuss the preliminary of cell biology required to proceed to implement our proposed method. This project presents a new automated approach for blood Cancer detection and analysis from a given photograph of patient’s cancer affected blood sample. The proposed method is using image improvement, image segmentation for segmenting the different cells of blood, edge detection for detecting the boundary, size, and shape of the cells and finally Clustering for final decision of blood cancer based on the number of different cells.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Monday, 13 September 2021
Lung Nodule Detection Using Machine Learning Matlab Project With Source Code | IEEE Based Projects
ABSTRACT
Lung nodule prevalence is one of the highest of cancers, at 18 %. One of the first steps in lung nodule diagnosis is sampling of lung tissues or biopsy. These tissue samples are then microscopically analyzed. This procedure is taken once imaging tests indicate the presence of nodule cells in the chest. Lung nodule diagnosis using lung images. One of them is that doctor still relies on subjective visual observation. A medical specialist must do thorough observation and accurate analysis in detecting lung nodule in patients. Hence, there is need for a system that is capable for detecting lung nodule automatically from microscopic images of biopsy. This method will improve the accuracy and efficiency for lung nodule detection. The aim of this research is to design a lung nodule detection system based on analysis of microscopic image of biopsy using digital image processing. Microscopic images of biopsy are feature extracted and classified using support vector machine. This method is implemented to detection of lung nodule of lung samples.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com
Reversible Data Hiding for Image Steganography Matlab Project with Source Code
ABSTRACT
Reversible Data Hiding (RDH) techniques have gained popularity over the last two decades, where data is embedded in an image in such a way that the original image can be restored. Earlier works on RDH was based on the Image Histogram Modification that uses the peak point to embed data in the image. More recent works focus on the Difference Image Histogram Modification that exploits the fact that the neighboring pixels of an image are highly correlated and therefore the difference of image makes more space to embed large amount of data. In this project we propose a framework to increase the embedding capacity of reversible data hiding techniques that use a difference of image to embed data. The main idea is that, instead of taking the difference of the neighboring pixels, we rearrange the columns (or rows) of the image in a way that enhances the smooth regions of an image. Any difference based technique to embed data can then be used in the transformed image. The proposed method is applied on different types of images including textures, patterns and publicly available images.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Character Recognition Using Python Project with Source Code | IEEE Based Projects
ABSTRACT
Optical character recognition (OCR) is becoming a powerful tool in the field of Character Recognition, now a days. In the existing globalized environment, OCR can play a vital role in different application fields. Basically, OCR technique converts images into editable format. This technique converts images in the form of documents such as we can edit, modify and store data more safely for longtime. This paper presents basic of OCR technique with its components such as pre-processing, Feature Extraction, Classification, post-processing etc. There are various techniques have been implemented for the recognition of character. This Review also discusses different ideas implemented earlier for recognition of a character. This paper may act as a supportive material for those who wish to know about OCR. Now a days, globalization is reaching to a great level. In this globalized environment, character recognition techniques also getting a valuable demand in number of application areas. OCR is an effective technique which converts image into suitable format such that data can be edit, modify and stored. This technique performs several operations such as, scans the input image, processes over the scanned image thereby image gets converted into portable formats .For instance, the hard copy of old historical books, novels, etc. .cannot be stored safely for a long time. Rather, its safety has limitations. If we apply OCR technique for such cases, the different historical documents can be stored, modified for a longtime. OCR also having variety of applications in almost all fields, including security. OCR implementation helps us to edit, store and process over the scanned data more effectively. User can handle the stored data whenever he wants with the internet support. So Optical character recognition is most successful application used in pattern recognition.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com
Friday, 23 July 2021
Python Code for Soybean Leaf Diseases Detection Using Deep Learning || Final Year Projects
ABSTRACT
India is an agricultural country and soybean production is one of the major sources of earning. Due to the major factors like diseases, pest attacks, and sudden changes in the weather condition, the productivity of the soybean crop decreases. Automatic detection of soybean plant diseases is essential to detect the symptoms of soybean diseases as early as they appear on the growing stage. This project proposed a methodology for the analysis and detection of soybean plant leaf diseases using recent digital image processing techniques. In this project, experimental results demonstrate that the proposed method can successfully detect and classify the major soybean diseases like Soybean Rust, Powdery Mildew, Frogeye Leaf Spot, Downy Mildew, etc.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com
Matlab Code for Emotion Recognition from Speech Signal || IEEE Based Projects || Final Year Projects
ABSTRACT
Emotion Recognition is a recent research topic in the field of Human Computer Interaction Intelligence and mostly used to develop wide range of applications such as stress management for call centre employee, and learning & gaming software, In E-learning field, identifying students emotion timely and making appropriate treatment can enhance the quality of teaching. Main aim of HCI is to achieve a more natural interaction between machine and humans. HCI is an emerging field using which we can improve the interactions between users and computers by making computers more respond able to the user’s needs. Today’s HCI system has been developed to identify who is speaking or what he/she is speaking. If in the HCI system, the computers are given an ability to detect human emotions then they can know how he/she is speaking and can respond accurately and naturally like humans do. In this project methodology for emotion recognition from speech signal is presented. Here, some of acoustic features are extracted from speech signal to analyze the characteristics and behavior of speech. The system is used to recognize the basic emotions. It can serve as a basis for further designing an application for human like interaction with machines through natural language processing and improving the efficiency of emotion. In this format, energy, Mel Frequency Cepstral Coefficients (MFCC) has been used for feature extraction from the speech signal. Support Vector Machine (SVM) are used for recognition of emotional states. English datasets are used for analysis of emotions with SVM Kernel functions.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Sunday, 27 June 2021
Facial Emotion Recognition Using Image Processing | Python Project Source Code | IEEE Based Project
ABSTRACT
This project objective is to introduce needs and applications of facial expression recognition. Between Verbal & Non-Verbal form of communication facial expression is form of non-verbal communication but it plays pivotal role. It express human perspective or filling & his or her mental situation. A big research has been addressed to enhance Human Computer Interaction (HCI) over two decades. This project includes introduction of facial emotion recognition system, Application, comparative study of popular face expression recognition techniques & phases of automatic facial expression recognition system. Emotional aspects have huge impact on Social intelligence like communication understanding, decision making and also helps in understanding behavioral aspect of human. Emotion play pivotal role during communication. Emotion recognition is carried out in diverse way, it may be verbal or non-verbal .Voice (Audible) is verbal form of communication & Facial expression, action, body postures and gesture is non-verbal form of communication. While communicating only 7% effect of message is contributes by verbal part as a whole, 38% by vocal part and 55% effect of the speaker’s message is contributed by facial expression. For that reason automated & real time facial expression would play important role in human and machine interaction. Facial expression recognition would be useful from human facilities to clinical practices. Analysis of facial expression plays fundamental roles for applications which are based on emotion recognition like Human Computer Interaction (HCI), Social Robot, Animation, Alert System & Pain monitoring for patients.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com
Thursday, 1 April 2021
Image Encryption Decryption Using Chaotic System Matlab Project With Source Code
ABSTRACT
Due to the rapid rise of telemedicine, a lot of patients’ information will be transmitted through the Internet. However, the patients’ information is related to personal privacy, therefore, patients’ information needs to be encrypted when transmitted and stored. Medical image encryption is a part of it. Due to the informative fine features of medical images, a common image encryption algorithm is no longer applied. Common encryption algorithm has a single theory based on chaos image encryption algorithm, other encryption algorithms are based on information entropy. However, the images processed with these cipher text encryption algorithm are cyclical, the outline is clear and the anti-tamper capability is not strong. In view of the bit being the smallest measure unit of pixel, in order to overcome the weakness from above algorithm, and take the advantage of the chaotic system, this project present a chaotic medical image encryption algorithm based on bit-plane decomposition.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Audio Steganography for Hiding Audio In Audio Using Matlab Project Source Code | IEEE Based Projects
ABSTRACT
Steganography is one of the methods of secret communication that hides the existence of message so that a viewer cannot detect the transmission of message and hence cannot try to Extract it. It is the process of embedding secret data in the cover Audio without significant changes to the cover audio. These algorithms keep the messages from stealing, destroying from unintended users on the internet and hence provide security. In this project we perform Audio Steganography Hiding Secret audio In Cover audio using matlab.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Wednesday, 31 March 2021
PYTHON PROJECTS WITH SOURCE CODE
>> Soybean Plan Leaf Diseases Detection Using Neural Network Python Project Source Code
>> Optical Character Recognition Using Image Processing Python OpenCV Project with Source Code
>> Audio Steganography Using Python Project Source Code || Hiding Text In Audio Using Python Project
>> Image Compression Using Python Project || Image Compression Using Python Project With Source Code
>> Python Code On Image Steganography For Hiding Secret Image In Cover Image
>> Message Cryptography Using Python Project with Source Code
>> Real Time Face Recognition Using Python | Python Code for Face Recognition Using WebCam
>> Python Code for Social Distance Detection (Covid19) Full Project With Source Code
>> Python Code for Digit Recognition Using Image Processing Full Project Source Code
>> AES Based Message Encryption and Decryption Using Python Project Source Code
>> Barcode Recognition Using Python Project Source Code
>> Image Steganography Using Python Source Code - Hiding Message in Image Using Python Project
FingerNail Disease Detection Using Image Processing Matlab Project Source Code | IEEE Based Projects
ABSTRACT
This project gives idea to predict diseases using the color of the nail at early stage of diagnosis. The main aim of our project is to analyze the disease without causing harm to humans. In earlier traditional system of disease detection, doctors observe the nails of patients and will predict the disease. Many diseases can be identified by analyzing nails of patients. But it is difficult for human eyes to differentiate the slight changes in color. So it is less accurate and time consuming. Our proposed system can be quite useful to overcome this issue since it is fully computer based. The input to the proposed system is image of nail. The system will process the nail image and will extract the nail’s features to diagnose the disease. Human nail consist of various features, our proposed system uses nail color changes to diagnose the disease. Here, first training set data is prepared from nail images of patients with specific diseases. This training data set is compared with extracted feature from input nail image to obtain the result. In our experiment, we found that training set data are correctly matched with color feature of nail image results. It is focused on the system of image recognition on the basis of color analysis. The proposed system is based on the algorithm which automatically extracts only nails area from scanned back side of palm (Region of Interest). These selected pixels are processed for further analysis using median filters. The system is fully computer based, so even small discontinuities in color values are observed, and we can detect color changes in the initial stage of disease.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com
Blood Cancer Detection Using Neural Network | Matlab Project Source Code | IEEE Based Project
ABSTRACT
Blood cancer is the most prevalent and it is very much dangerous among all type of cancers. Early detection of blood cancer has the potential to reduce mortality and morbidity. There are many diagnostic technologies and tests to diagnose blood cancer. However many of these tests are extremely complex and subjective and depend heavily on the experience of the technician. To obviate these problems, image processing techniques and a fuzzy inference system is use in this study as promising modalities for detection of different types of blood cancer. The accuracy rate of the diagnosis of blood cancer by using the fuzzy system will be yield a slightly higher rate of accuracy then other traditional methods and will reduce the effort and time. We first discuss the preliminary of cell biology required to proceed to implement our proposed method. This project presents a new automated approach for blood Cancer detection and analysis from a given photograph of patient’s cancer affected blood sample. The proposed method is using Wavelet Transformation for image improvement, image segmentation for segmenting the different cells of blood, edge detection for detecting the boundary, size, and shape of the cells and finally Clustering for final decision of blood cancer based on the number of different cells.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Face Emotion Recognition Using Image Processing | Python Project Source Code | IEEE Based Project
ABSTRACT
This project objective is to introduce needs and applications of facial expression recognition. Between Verbal & Non-Verbal form of communication facial expression is form of non-verbal communication but it plays pivotal role. It express human perspective or filling & his or her mental situation. A big research has been addressed to enhance Human Computer Interaction (HCI) over two decades. This project includes introduction of facial emotion recognition system, Application, comparative study of popular face expression recognition techniques & phases of automatic facial expression recognition system. Emotional aspects have huge impact on Social intelligence like communication understanding, decision making and also helps in understanding behavioral aspect of human. Emotion play pivotal role during communication. Emotion recognition is carried out in diverse way, it may be verbal or non-verbal .Voice (Audible) is verbal form of communication & Facial expression, action, body postures and gesture is non-verbal form of communication. While communicating only 7% effect of message is contributes by verbal part as a whole, 38% by vocal part and 55% effect of the speaker’s message is contributed by facial expression. For that reason automated & real time facial expression would play important role in human and machine interaction. Facial expression recognition would be useful from human facilities to clinical practices. Analysis of facial expression plays fundamental roles for applications which are based on emotion recognition like Human Computer Interaction (HCI), Social Robot, Animation, Alert System & Pain monitoring for patients.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com
Tuesday, 23 March 2021
Python Code On Image Watermarking Full Project With Source Code | IEEE Based Project | Final Year Project
ABSTRACT
Digital Image watermarking is a technology for embedding various types of information in digital content. In general, information for protecting copyrights and proving the validity of data is embedded as a watermark. A digital watermark is a digital signal or pattern inserted into digital content. The digital content could be a still image, an audio clip, a video clip, a text document, or some form of digital data that the creator or owner would like to protect. The main purpose of the watermark is to identify who the owner of the digital data is, but it can also identify the intended recipient. The Image watermarking is most popular method for copyright protection by discrete wavelet transform which performs two level decomposition of original cover image and watermark image is embedded in lowest level sub band of cover image.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com
Brain Tumor Detection Using Image Processing Python Project With Source Code | IEEE Based Projects
ABSTRACT
Brain tumors are the most common issue in children. Approximately 3,410 children and adolescents under age 20 are diagnosed with primary brain tumors each year. Brain tumors, either malignant or benign, that originate in the cells of the brain. The conventional method of detection and classification of brain tumor is by human inspection with the use of medical resonant brain images. But it is impractical when large amounts of data is to be diagnosed and to be reproducible. And also the operator assisted classification leads to false predictions and may also lead to false diagnose. Medical Resonance images contain a noise caused by operator performance which can lead to serious inaccuracies classification. In this work we used Brain Tumor Detection Using Image Processing.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Tuesday, 9 March 2021
Python Code for Plant Disease Detection Using CNN Convolutional Neural Network Full Source Code || IEEE Based Projects
ABSTRACT
The detection and classification of plant diseases are the crucial factors in plant production and the reduction of losses in crop yield. This project proposes an approach for plant leaf disease detection and classification on plants using image processing. The algorithm presented has three basic steps: Image Pre-processing and analysis Recognition of plant disease. The plant disease diagnosis is restricted by person’s visual capabilities as it is microscopic in nature. Due to optical nature of plant monitoring task, computer visualization methods are adopted in plant disease recognition. The aim is to detect the symptoms of the disease occurred in leaves in an accurate way. Once the captured image is pre-processed, the various properties of the plant leaf such as intensity, color and size are extracted and sent to with Convolutional Neural Network CNN for classification.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Matlab Code for Key Based AES Image Encryption Decryption | AES Based Image Encryption Using Matlab Project
ABSTRACT
During the last decade information security has become the major issue. The encrypting and decrypting of the data has been widely investigated because the demand for the better encryption and decryption of the data is gradually increased for getting the better security for the communication between the devices more privately. The Image Encryption Decryption play a major role for the fulfillment for this demand. The purpose of this project is to provide the better as well as more secure communication system by enhancing the strength of Advance Encryption Standard (AES) algorithm. AES algorithm was known for providing the best security without any limitations.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Monday, 22 February 2021
Top 10 Biomedical Projects With Source Code | Top 10 Final Year Projects With Source Code
1. Liver Cancer Detection Using Image Processing
2. Fingernail Disease Detection Using Image Processing
3. Skin Disease Detection Using Image Processing Matlab Project Code
4. Types of Brain Tumor Detection Using Matlab Project Source Code
5. Breast Cancer Detection Using Image Processing Matlab Project With Source Code
6. Blood Group Detection Using Image Processing Matlab Project Source Code
7. Brain Tumor Detection Using CNN Matlab Project Source Code
8. Malaria Detection from Blood Cell Using Neural Network Matlab Project Source Code
9. Leukemia Blood Cancer Detection Using Image Processing Matlab Project With Code
10. Diabetic Retinopathy Detection Using Neural Network Matlab Project Code
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Hiding Audio In Video (Video Steganography) Using Matlab Project with Source Code
ABSTRACT
Steganography is one of the methods of secret communication that hides the existence of message so that a viewer cannot detect the transmission of message and hence cannot try to Extract it. It is the process of embedding secret audio file in the cover Video file without significant changes to the cover video. These algorithms keep the messages from stealing, destroying from unintended users on the internet and hence provide security. In this project we perform Video Steganography for Hiding Secret Audio In cover video using matlab.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Image Retrieval Using Image Processing Matlab Project With Source Code
ABSTRACT
Content based image retrieval utilizes representations of features that are automatically extracted from the images themselves. All most all of the current CBIR systems allow for querying by example, a technique wherein an image (or part of an image) is selected by the user as the query. The system extracts the feature of the query image, searches the database for images with similar features, and exhibits relevant images to the user in order of similarity to the query. In this context, content includes among other features, perceptual properties such as texture, color, shape, and spatial relationships. Many CBIR systems have been developed that compare, analyze and retrieve images based on one or more of these features. Some systems have achieved various degrees of success by combining both content based and text based retrieval. In all cases, however, there has been no definitive conclusion as to what features provide the best retrieval. In this project we are retrieving the images similar to the query image.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Image Cryptography Using AES Algorithm Matlab Project With Source Code
ABSTRACT
Images are sent over an insecure transmission channel from different sources, some image data contains secret data, some images itself are highly confidential hence, securing them from any attack is essentially required. One way to provide image data security is by using Visual Cryptography. Visual cryptography is a technique in which visual information is enciphered in such a way that no one able to identify the image during transmission. One of the well-known visual cryptographic schemes has been ascribe to Moni Naor and Adi Shamir in 1994. During data transmission, data can be transmitted in the form of text, image, audio and video, hence securing all kinds of data is most essential in today’s era. Securing Image data is one of the major concern and a complex term. Various visual cryptographic techniques have been developed for confidentiality, authenticity and integrity of images during transmission and when it is received at other end. This project proposes an Image cryptography technique on the basis of AES Algorithm.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Wednesday, 3 February 2021
MATLAB PROJECTS WITH SOURCE CODE
>> Lung Cancer Detection Using Neural Network Matlab Project With Source Code
>> Rice Leaf Disease Detection using Image Processing Matlab Project with Source Code
>> Matlab Code for Breast Cancer Detection using Neural Network | IEEE Based Project
>> Audio Steganography For Data Hiding In Audio Using Matlab Project With Source Code
>> Matlab Code for Grape Leaf Disease Detection using Image Processing
>> Automated Blood Cancer Detection (Leukemia Detection) Using Image Processing
>> Matlab Code On Fruit Disease Detection and Classification Using Image Processing
>> Speech Emotion Recognition Using Matlab Project Source Code
>> Matlab Code for Audio Steganography (Secrete Information hiding in Audio)
>> Brain Tumor Detection and Classification Matlab Project Source Code
>> Matlab Code for Prostate Cancer Detection Using Image Processing
>> Image Watermarking Using DWT and DCT Matlab Project with Source Code
>> Image Enhancement Using Histogram Equalization
>> Medical Image Fusion Using Wavelet Transform and PCA
>> Image Compression Using EZW Embedded Zero-Tree Wavelet
>> Digit Recognition Using Neural Network Matlab Project with Source Code
>> Lung Cancer Detection using Image Processing Matlab Project Source Code
>> Image Compression using SPHIT and Improved SPIHT Algorithm
>> Matlab Code for Blood Type Detection Using Image Processing
>> Early Stage Brain Tumor Detection and Classification using Matlab Project Code
>> Content Based Image Retrieval Systems (CBIR) using Image Processing Matlab Project
>> JPEG2000 Steganography Scheme for Baseline System
>> Image Steganography Using Matlab Project Code
>> Image Fusion On MRI And CT Image Using Wavelet Transform Matlab Project with Source Code
>> Audio Noise Reduction from Audio Signals and Speech Signals Using Wavelet Transform
Saturday, 16 January 2021
Matlab Code for Image Compression Using Huffman Algorithm Full Project Source Code
ABSTRACT
The lossless compression is that allows the original data to be perfectly reconstructed from the compressed data. Lossless compression programs do two things in sequence: the first step generates a statistical model for the input data, and the second step uses this model to map input data to bit sequences in such a way that probable. The main objective of image compression is to decrease the redundancy of the image data which helps in increasing the capacity of storage and efficient transmission. Image compression aids in decreasing the size in bytes of a digital image without degrading the quality of the image to an undesirable level. Image compression plays an important role in computer storage and transmission. The purpose of data compression is that we can reduce the size of data to save storage and reduce time for transmission. Image compression is a result of applying data compression to the digital image.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Message Cryptography Using Python Project with Source Code
ABSTRACT
Message security is an utmost concern in the web attacks are become more serious. The Message encryption and decryption has applications in internet communication, military communication, medical imaging, multimedia systems, tele-medicine, etc. To make the data secure from various attacks the data must be encrypted before it is transmitting. Absolute protection is a difficult issue to maintain the confidentiality of Message through their transmission over open channels such as internet or networks and is a major concern in the media, so Data Cryptography becomes an area of attraction and interest of research in the field of information security. The project offer proposed system that provides a special kinds of image Encryption data security, Cryptography for encrypted Message to extract. This approach provides high security and it will be suitable for secured transmission of data over the networks or Internet.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Age and Gender Recognition using WebCam Python Project Source Code || Age and Gender Recognition using Deep Learning
ABSTRACT
Automatic age and gender classification has become relevant to an increasing amount of applications, particularly since the rise of social platforms and social media. Nevertheless, performance of existing methods on real-world images is still significantly lacking, especially when compared to the tremendous leaps in performance recently reported for the related task of face recognition. In this project we show that by learning representations through the use of deep-convolutional neural networks (CNN), a significant increase in performance can be obtained on these tasks. To this end, we propose a simple convolutional net architecture that can be used even when the amount of learning data is limited. We evaluate our method on the recent Audience benchmark for age and gender estimation and show it to dramatically outperform current state-of-the-art methods.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
Audio Steganography Using Python Project Source Code || Hiding Text In Audio Using Python Project
ABSTRACT
Steganography is one of the best data hiding technique in the world which can be used to hide data without its presence felt. In today’s digital world most of us communicate via use of electronic media or internet. Most people among us remain unaware about the data loss or data theft which can happen on online transmission of data or message. Valuable information including personal data, messages transmitted through internet is vulnerable to hackers who may steal or decrypt our data or messages. This project is about enhancing the data or message security with use of Audio Steganography to hide the message into audio files. The message hidden by this application is less vulnerable to be stolen than other similar applications. This is due to following reasons: Firstly files are taken to hide high amount of message which enhance information hiding capacity. Secondly before being hidden, the message is broken into parts and shuffled randomly based on permutation generated at runtime so even if the LSB gets encountered the message is still unarranged and meaningless which enhances its security. This application is capable to carry large amount of information with greater security.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email id: roshanphelonde@rediffmail.com
