Haze Removal using Image Processing Matlab Project with Source Code

ABSTRACT

           Haze causes problems in various computer vision and image processing based applications as it diminishes the scene's visibility. The air light and attenuation are two main phenomena responsible for haze formation .The air light enhance the whiteness in the scene and contrast get reduced by attenuation. Haze removal techniques helps in recovering the contrast and color of the scene. These techniques have found many applications in the area of image processing such as consumer electronics, object detection, outdoor surveillance etc. 

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Mr. Roshan P. Helonde

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Facial Expression Recognition using Matlab Project with Source Code

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.

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Mr. Roshan P. Helonde

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Fish Disease Detection using Neural Network Matlab Project with Source Code

ABSTRACT

             There is a lot of expert knowledge in fish disease diagnostic process. Aimed at the drawbacks of expert diagnosis such as low level of intelligence and poor practicality, a new structure of fish disease diagnostic expert system based on neural networks is proposed. The diagnosis system uses the old cases of fish disease to train the neural network, and the disease diagnosis is achieved through the trained neural network. This method can realize the diagnosis of fish disease timely and rapidly, and provide a new effective method to the development of fish disease diagnosis system. 

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Mr. Roshan P. Helonde

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Bone Fracture Detection using Neural Network Matlab Project with source Code

ABSTRACT

            Analysis of medical images plays a very important role in clinical decision making. For a long time it has required extensive involvement of a human expert. However, recent progress in data mining techniques, especially in machine learning, allows for creating decision models and support systems that help to automatise this task and provide clinicians with patient-specific therapeutic and diagnostic suggestions. In this project, we describe a study aimed at building a decision model (a classifier) that would predict the type of treatment (surgical vs. non-surgical) for patients with bone fractures based on their X-ray images. We consider two types of features extracted from images (structural and textural) and used them to construct multiple classifiers that are later evaluated in a computational experiment. Structural features are computed by applying the Hough transform, while textural information is obtained from Gray-level occurrence matrix. In research reported by other authors structural and textural features were typically considered separately. Our findings show that while structural features have better predictive capabilities, they can benefit from combining them with textural ones.

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Mr. Roshan P. Helonde

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Mango Plant Disease Detection Using Neural Network Matlab Project Code

ABSTRACT

            The mango fruit is popular because of its wide range of adaptability, high nutritional value, different variety, delicious taste and excellent flavor. The fruit contains vitamin A and vitamin C in a rich extent. The crop is prone to diseases like Powdery mildew, Anthracnose, Red Rust, Golmich, etc. Disorders may also impact the plant in the absence of effective case and control measures. These include change of form, biennial bearing, fall of fruit, black top, clustering, etc. The farmer must consult and take professional support for the prevention / control of diseases and crop disorder. New techniques of detecting mango disease are required to promote better control to avoid this crisis. By considering this, project describes image recognition which provides cost effective and scalable disease detection technology. Paper further describes new deep learning models which give an opportunity for easy deployment of this technology.

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Mr. Roshan P. Helonde

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RBC and WBC Detection and Counting using Image Processing Matlab project code

ABSTRACT

              Detection and Counting of blood cells are considered as an important step that helps to extract features to diagnose some specific diseases like malaria or leukemia. The manual counting of white blood cells (WBCs) and red blood cells (RBCs) in microscopic images is an extremely tedious, time consuming, and inaccurate process. Automatic analysis will allow hematologist experts to perform faster and more accurately. The proposed method uses an iterative structured circle detection algorithm for the segmentation and counting of WBCs and RBCs. The separation of WBCs from RBCs was achieved by thresholding, and specific preprocessing steps were developed for each cell type. Counting was performed for each image using the proposed method based on modified circle detection, which automatically counted the cells.

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Mr. Roshan P. Helonde

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Signature Verification on Bank Cheque using Image processing Matlab Project Code

ABSTRACT

            The area of Signature Verification has been broadly researched in the last decades, but remains an open research problem. The objective of signature verification systems is to discriminate if a given signature is genuine produced by the claimed individual, or a forgery produced by an impostor. This has demonstrated to be a challenging task, in particular in the offline static scenario, that uses images of scanned signatures, where the dynamic information about the signing process is not available. Many advancements have been proposed in the literature in the last 5-10 years, most notably the application is to learn feature representations from signature images. In this project, we present how the problem has been handled in the past few decades, analyse the recent advancements in the field, and the potential directions for future research.

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Mr. Roshan P. Helonde

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Text Image Watermarking using Image Processing Matlab Project code

ABSTRACT

            Multimedia security is a major issue. Images, video, audio, text files are losing their credibility day by day as they can be distorted or manipulated by using several tools. Ensuring the authenticity and integrity of digital media is a major issue. The manipulation made by forgery tools are so smoothly done that we don’t even suspect that forgery may be involved in digital content. Multimedia data is facing several issues related to illegal distribution, duplication and manipulation of information conveyed by them. The digital watermarking technique plays an important role in protecting digital content. In this project, On the basis of their operating principles different watermarking techniques are categorised. Attacks, applications and requirements related to watermarking techniques are also discussed. Different watermarking techniques proposed by researchers for protecting copyrights of digital media are presented which are based on spatial and frequency domain. Frequency domain are getting much more attention due to use of wavelets which

have high degree of resemblance to human visual system. In digital watermarking, secret information is embedded with original data for maintaining ownership rights of the digital content. Spatial domain watermarking techniques work over pixel characteristics and frequency domain watermarks concerned about different transformations that can be used with digital content. Imperceptibility, robustness, security, complexity and capacity are some requirements of the digital watermarking which completely depends on the algorithm used for watermarking.

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Mr. Roshan P. Helonde

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Fake Biometric Recognition using Image Processing Matlab Project Code || IEEE Based Project

ABSTRACT

              Achieving high security in varied areas, biometric system has become common analysis space over past decades. Biometric system provides machine-controlled personal identification supported distinctive features of an individual. Biometric system depends on distinguishing every individual on the premise of their physiological options Face, Finger Print, Palm Print. Security will primarily be achieved by three factors: password or pin, sensible token or access card, biometric technology. Out of those three ways, biometric system is best as a result of user ought not to remember (password or pin) or keep something (smart token or access card) for identification or verification. In this project present a novel approach Biometric Recognition Using Face, Palm, Retina and Signature.

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Mr. Roshan P. Helonde

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Marathi Character Recognition using neural Network Matlab Project Source Code

ABSTRACT

          Marathi character can be converted in to the digital information using Marathi character Recognition, which is the ability of a computer to receive and interpret handwritten input from documents. Marathi Characters are more complex for recognition due to presence of header line, conjunct characters and similarity in shapes of multiple characters. For Marathi Character recognition using neural network various approaches has been proposed. In general the process involves phases as: Scanning, Pre-processing, Feature Extraction and Recognition. Preprocessing includes noise reduction and normalisation Feature extraction includes extracting some useful information out of the pre-processed image in the form of a feature vector. Artificial neural network is used for classification. 

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Mr. Roshan P. Helonde

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Maize Plant Disease Detection using Image Processing Matlab Project Source Code

ABSTRACT

            Plant leaf diseases can affect plant leaves to a certain extent that the plants can collapse and die completely. These diseases may drastically decrease the supply of vegetables and fruits to the market, and result in a low agricultural economy. In the literature, different laboratory methods of plant leaf disease detection have been used. These methods were time consuming and could not cover large areas for the detection of leaf diseases. This study infiltrates through the facilitated principles of the Support Vector Machine (SVM) in order to model a network for image recognition and classification of these diseases. SVM network that recognised and classified images of the maize leaf diseases that were collected by acquisition process. A novel way of training and methodology was used to expedite a quick and easy implementation of the system in practice. The developed model was able to recognise three different types of maize leaf diseases out of healthy leaves.

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Mr. Roshan P. Helonde

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Breast Cancer Detection using Image Processing Matlab Project Source Code

ABSTRACT

              The World Health Organization's International agency for Research on Cancer in Lyon, France, estimates that more than 150 000 women worldwide die of breast cancer each year. The breast cancer is one among the top three cancers in American women. In United States, the American Cancer Society estimates that, 215 990 new cases of breast carcinoma has been diagnosed, in 2004. It is the leading cause of death due to cancer in women under the age of 65. However, cervical cancer is still number one in rural India. Although the incidence is lower in India than in the developed countries, the burden of breast cancer in India is alarming. Organ chlorines are considered a possible cause for hormone-dependent cancers . Detection of early and subtle signs of breast cancer requires high-quality images and skilled mammographic interpretation. In order to detect early onset of cancers in breast screening, it is essential to have high-quality images. Radiologists reading mammograms should be trained in the recognition of the signs of early onset of, which may be subtle and may not show typical malignant features. Mammography screening programs have shown to be effective in decreasing breast cancer mortality through the detection and treatment of early onset of breast cancers. Emotional disturbances are known to occur in patient's suffering from malignant diseases even after treatment. This is mainly because of a fear of death, which modifies Quality Of Life (QOL). Most imaging studies and biopsies of the breast are conducted using mammography or ultrasound, in some cases, magnetic resonance (MR) imaging . Although by now some progress has been achieved, there are still remaining challenges and directions for future research such as developing better enhancement and segmentation algorithms.

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Mr. Roshan P. Helonde

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Rust Defect Detection and Evaluation Of Steel Coating Conditions using Matlab Project Source Code

ABSTRACT

               In this project we propose a methodology for assessment of coating condition of bridge images. The defect recognition algorithm includes conversion of captured images into grey level; these grey level images are grouped into defective & non defective group. Further that is processed to plot correspondence map. The correspondence map is measure of matching image. Straight line with 450 in correspondence map indicates no defect in scene image. In contrast if correspondence map produces nonlinear image it indicates defect (rust) in scene image. The nonlinear shape of grey level distribution in correspondence map can be analyzed by calculating Eigen values. Two similar images will produce smaller Eigen value (approximately zero), whereas it will be distinctly large for dissimilar images.

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Mr. Roshan P. Helonde

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Handwritten Character Recognition using Image Processing matlab project source code

ABSTRACT

             Recognition of Handwritten text has been one of the active and challenging areas of research in the field of image processing and pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. In this project we focus on recognition of English alphabet in a given scanned text document with the help of Neural Networks. We tried to recognise handwritten characters by projecting them on different sized grids. The first step is image acquisition which acquires the scanned image followed by noise filtering, smoothing and normalisation of scanned image, rendering image suitable for segmentation where image is decomposed into sub images. Feature Extraction improves recognition rate and mis classification.

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Mr. Roshan P. Helonde

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Hand Gesture Recognition using image processing matlab project with source code

ABSTRACT

              Sign language is the basic communication method for those who suffer from hearing impairment. The primary component of a sign language is hand gestures. Gesturing is an instinctive way of communication to present a specific meaning. Sign language is the visual manual modality to convey meaning which is quite similar to the hand gestures. Language is expressed via the manual sign-stream in combination with non-manual elements. Sign languages are full-fledged natural languages with their own grammar and lexicon. Gesture is a distinct form of sign language which involves movement of body such as hands or face to express the meaning. Hand gesture has received a greater importance over the last few years because to remove the barrier of communication between mute people and normal people. It is an object consists of distinct features to extract and recognise the gestures or signs exactly, therefore gesture recognition presents a most difficult and challenging tasks in the fields of image processing, computer vision and image analysis. The images are subjected to image processing steps.  In order to achieve a better accuracy the image processing and machine learning techniques are used.

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Mr. Roshan P. Helonde

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Corn Disease Detection using Image Processing Matlab project with Source Code

ABSTRACT

            Plant leaf diseases can affect plant leaves to a certain extent that the plants can collapse and die completely. These diseases may drastically decrease the supply of vegetables and fruits to the market, and result in a low agricultural economy. In the literature, different laboratory methods of plant leaf disease detection have been used. These methods were time consuming and could not cover large areas for the detection of leaf diseases. A novel way of training and methodology was used to expedite a quick and easy implementation of the system in practice. The developed model was able to recognise different types of Corn leaf diseases out of healthy leaves, Corn Leaf Blight (Exserohilum), Common Rust (Puccinia Sorghi) and Corn Leaf Spot (Cercospora) diseases were chosen for this study as they affect most parts of Corn Plant.

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Mr. Roshan P. Helonde

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WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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