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.

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Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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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.

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Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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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

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Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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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. 

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Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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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.

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Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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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

>> Facial Emotion Recognition Using Image Processing | Python Project Source Code | IEEE Based Project

>> Python Code On Image Watermarking Full Project With Source Code | IEEE Based Project | Final Year Project

>> Audio Steganography Using Python Project Source Code || Hiding Text In Audio Using Python Project

>> Image Steganography for Hiding Message in Image Using Image Processing | Python Project Source Code | IEEE Based Project

>> Image Compression Using Python Project || Image Compression Using Python Project With Source Code

>> Brain Tumor Detection Using Image Processing Python Project With Source Code | IEEE Based Projects

>> Image Encryption Decryption Using AES Algorithm Python Project With Source Code | IEEE Based Projects

>> Python Code On Image Steganography For Hiding Secret Image In Cover Image

>> Plant Disease Detection Using Convolutional Neural Network CNN Full Python  Project With Source Code || IEEE Based Projects

>> Age and Gender Recognition using WebCam Python Project Source Code || Age and Gender Recognition using Deep Learning

>> 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

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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

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Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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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

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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

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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

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Contact: 

Prof. Roshan P. Helonde 

Mobile: +91-7276355704 

WhatsApp: +91-7276355704 

Email: roshanphelonde@rediffmail.com

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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.

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Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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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

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Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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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.

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Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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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

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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

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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

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Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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