Color Based Image Retrieval System Using Image Processing Matlab Project with Source Code

ABSTRACT

                  Advances in the data storage and image acquisition technologies have enabled the creation of large datasets. It is necessary to develop appropriate information systems to efficiently manage these collections. The most common approaches use Color-Based Image Retrieval (CBIR) system. The goal of CBIR system is to support image retrieval based on color. In a color based image retrieval system querying can be done by a query image. The goal is to find the images most resembling the query. In this Project we mainly focused on color histogram-based method. Color is most intuitive feature of an image and to describe colors generally histograms are adopted. Histogram methods have the advantages of speediness, low demand of memory space. Color features are the most important elements enabling human to recognize images. For categorizing images, color features can provide powerful information and they are used for image retrieval, so color based image retrieval is mostly used method. Color features of the images are generally represented by color histograms. Before using color histograms, however, we need to select and quantify a color space model and choose a distance metric. 

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Prof. Roshan P. Helonde

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Email: roshanphelonde@rediffmail.com

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Brain Tumor Detection Using Rough Set Theory on Dicom Images Matlab Project with Source Code

ABSTRACT

                     Brain tumor is a life threatening disease and its early detection is very important to save life. The tumor region can be detected by segmentation of brain Magnetic Resonance Image (MRI). Once a brain tumor is clinically suspected, radiologic evaluation is required to determine the location, the extent of the tumor, and its relationship to the surrounding structures. This information is very important and critical in deciding between the different forms of therapy such as surgery, radiation, and chemotherapy. The segmentation must be fast and accurate for the diagnosis purpose. Manual segmentation of brain tumors from magnetic resonance images is a tedious and time-consuming task. Also the accuracy depends upon the experience of expert. Hence, the computer aided automatic segmentation has become important. MRI scanned images offer valuable information regarding brain tissues. MRI scans provide very detailed diagnostic pictures of most of the important organs and tissues in our body. It is generally painless and noninvasive. It does not produce ionizing radiation. So MRI is one of the best clinical imaging modalities. Several automated segmentation algorithms have been proposed. But still segmentation of MRI brain image remains as a challenging problem due to its complexity and there is no standard algorithm that can produce satisfactory results. The  aim of this research work is to propose and implement an efficient system for tumor detection and classification. The different steps involved in this work are image pre-processing for noise removal, feature extraction, segmentation and classification

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Prof. Roshan P. Helonde

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Email: roshanphelonde@rediffmail.com

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Vehicle Number Plate Recognition Using Image Processing Matlab Project with Source Code

ABSTRACT

           This project presents Automatic Number Plate extraction, character segmentation and recognition for Indian vehicles. In India, number plate models are not followed strictly. Characters on plate are in different Indian languages, as well as in English. Due to variations in the representation of number plates, vehicle number plate extraction, character segmentation and recognition are crucial. We present the number plate extraction, character segmentation and recognition work, with english characters. Number plate extraction is done using Sobel filter, morphological operations and connected component analysis. Character segmentation is done by using connected component and vertical projection analysis. Automatic Number Plate Recognition (ANPR) system is an important technique, used in Intelligent Transportation System. ANPR is an advanced machine vision technology used to identify vehicles by their number plates without direct human intervention. It is an important area of research due to its many applications. The development of Intelligent Transportation System provides the data of vehicle numbers which can be used in follow up, analyses

and monitoring. ANPR is important in the area of traffic problems, highway toll collection, borders and custom security, premises where high security is needed, like Parliament, Legislative Assembly, and so on. The complexity of automatic number plate recognition work varies throughout the world. For the standard number plate, ANPR system is easier to read and recognize. In India this task becomes much difficult due to variation in plate model. 

                  The ANPR work is generally framed into the steps: Number plate extraction, character segmentation and character recognition. From the entire input image, only the number plate is detected and processed further in the next step of character segmentation. In character segmentation phase each and every character is isolated and segmented. Based on the selection of prominent features of characters, each character is recognized, in the character recognition phase. Extraction of number plate is difficult task, essentially due to: Number plates generally occupy a small portion of whole image; difference in number plate formats, and influence of environmental factors. This step affects the accuracy of character segmentation and recognition work. Different techniques are developed for number plate extraction. 

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Prof. Roshan P. Helonde

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Email: roshanphelonde@rediffmail.com

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Breast Cancer Detection Using Neural Networks Matlab Project with Source Code

ABSTRACT

                    Cancer is the major threat for human being health and its number of patients increasing word wide due to the global warming, even if there are new therapies and treatments proposed by research doctors, but level of cancer defines the ability of its cure. There are different types of cancers from which human being is suffering [male and female]. In this project we are focusing on breast cancer in women, rest allcancers are out of scope of this paper. Large number of women population is affected by the breast cancer. A different type of reasons causes the breast cancer such as X-Ray. For women’s, breast cancer is most common cancer, and it has been increasing since from last decade. The early detection of breast cancer helps to completely cure it through the treatment. The early detection is done by self-exam which can be done by woman in each month. This process is refereed as breast cancer early detection. However currently many hospitals and doctors uses the mammography test and resulted as effective technique for breast cancer early detection. The aim of this test is to perform early detection of breast cancer using characteristic masses detection as well as micro calcifications as these characteristics are considered as most important factor of breast cancer.

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Prof. Roshan P. Helonde

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Email: roshanphelonde@rediffmail.com

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LICENSE NUMBER PLATE RECOGNITION BY NEURAL NETWORKS AND IMAGE PROCESSING MATLAB PROJECT

ABSTRACT

                      The road becomes more pervasive, our country's road transport development, because of rapid labor management has not filled with actual needs, microelectronics, communications and computer technology in the transport sector of the application has greatly improved the traffic management efficiency. car license plates for automatic identification technology has been widely applied. car license plates automatically identify the entire process is divided into pre-processing, edge extraction, License Plate Positioning, character segmentation and character recognition 5 module, which character recognition process mainly consists of the following three components: 1) correctly to split text image area; 2) correct separation of a single text; 3) correctly identify a single character. The MATLAB software programming to achieve each and every part, and finally identify the license plate of a car. In the study of the same in which the issue of a concrete analysis, and processing. vehicle license plate recognition system as a whole is the main vehicle positioning and character recognition made up of two parts, one license plate positioning and can be divided into image pre-processing and edge extraction module and the licensing of the positioning and segmentation module; character recognition can be divided into character segmentation and feature extraction and a single character recognition two modules.

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Prof. Roshan P. Helonde

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Email: roshanphelonde@rediffmail.com

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A ROBUST DIGITAL IMAGE WATERMARKING BASED ON JOINT DWT AND DCT MATLAB PROJECT

ABSTRACT

The authenticity & copyright protection are two major problems in handling digital multimedia. The Image watermarking is most popular method for copyright protection by discrete Wavelet Transform (DWT) which performs 2 Level Decomposition of original (cover) image and watermark image is embedded in Lowest Level (LL) sub band of cover image. Inverse Discrete Wavelet Transform (IDWT) is used to recover original image from watermarked image. And Discrete Cosine Transform (DCT) which convert image into Blocks of M bits and then reconstruct using IDCT. In this paper we have compared watermarking using DWT & DWT-DCT methods performance analysis on basis of PSNR, Similarity factor of watermark and recovered watermark.

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Mr. Roshan P. Helonde

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WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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Automated Blood Cancer Detection Using Image Processing Matlab 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 Fuzzy Inference System for Final decision of blood cancer based on the number of different cells.

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Prof. Roshan P. Helonde

Mobile / WhatsApp:+91-7276355704

Email: roshanphelonde@rediffmail.com

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