Thursday 4 January 2018

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.

PROJECT OUTPUT
Contact:  
Prof. Roshan P. Helonde
Mobile / WhatsApp:+91-7276355704
Email: roshanphelonde@rediffmail.com

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.

PROJECT VIDEO

Contact:  
Mr. Roshan P. Helonde
Mobile:+91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com

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.

PROJECT OUTPUT


PROJECT VIDEO

Contact:  
Prof. Roshan P. Helonde
Mobile / WhatsApp:+91-7276355704
Email: roshanphelonde@rediffmail.com

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Prof. Roshan P. Helonde
Mobile / WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com

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