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

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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.

PROJECT VIDEO

Contact:  

Mr. Roshan P. Helonde

Mobile:+91-7276355704

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.

PROJECT OUTPUT

PROJECT VIDEO

Contact:  

Prof. Roshan P. Helonde

Mobile / WhatsApp:+91-7276355704

Email: roshanphelonde@rediffmail.com

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A LSB BASED STEGANOGRAPHY FOR VIDEO STREAM WITH ENHANCED SECURITY AND EMBEDDING/EXTRACTION Full Matlab Project

ABSTRACT

Video Steganography deals with hiding secret data or information within a video. In this paper, a hash based least significant bit (LSB) technique has been proposed. A spatial domain technique where the secret information is embedded in the LSB of the cover frames. Eight bits of the secret information is divided into 3,3,2 and embedded into the RGB pixel values of the cover frames respectively. A hash function is used to select the position of insertion in LSB bits. The proposed method is analyzed in terms of both Peak Signal to Noise Ratio (PSNR) compared to the original cover video as well as the Mean Square Error (MSE) measured between the original and stenographic files averaged over all video frames. Image Fidelity (IF) is also measured and the results show minimal degradation of the stenographic video file. The proposed technique is compared with existing LSB based Steganography and the results are found to be encouraging. An estimate of the embedding capacity of the technique in the test video file along with an application of the proposed method has also been presented.

PROJECT OUTPUT 

Contact:  

Prof. Roshan P. Helonde

Mobile / WhatsApp:+91-7276355704

Email: roshanphelonde@rediffmail.com

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Audio Noise Reduction from Audio Signals and Speech Signals Using Wavelet Transform Matlab Project

ABSTRACT

           Speech signal analysis is one of the important areas of research in multimedia applications. Discrete Wavelet technique is effectively reduces the unwanted higher or lower order frequency components in a speech signal. Wavelet-based algorithm for audio de-noising is worked out. We focused on audio signals corrupted with white Gaussian noise which is especially hard to remove because it is located in all frequencies. We use Discrete Wavelet transform (DWT) to transform noisy audio signal in wavelet domain. It is assumed that high amplitude DWT coefficients represent signal, and low amplitude coefficients represent noise. Using thresholding of coefficients and transforming them back to time domain it is possible to get audio signal with less noise. Our work has been modified by changing universal thresholding of coefficients which results with better audio signal. In this various parameters such as SNR, Elapsed Time, and Threshold value is analyzed on various types of wavelet techniques alike Coiflet, Daubechies, Symlet etc. In all these, best Daubechies as compared to SNR is more for Denoising and Elapsed Time is less than others for Soft thresholding. In using hard thresholding Symlet wavelet also works better than coiflet and Daubechies is best for all. Efficiency is 98.3 for de-noising audio signals which also gives us better results than various filters.

         Audio noise reduction system is the system that is used to remove the noise from the audio signals. Audio noise reduction systems can be divided into two basic approaches. The first approach is the complementary type which involves compressing the audio signal in some well-defined manner before it is recorded (primarily on tape). The second approach is the single-ended or non-complementary type which utilizes techniques to reduce the noise level already present in the source material—in essence a playback only noise reduction system. This approach is used by the LM1894 integrated circuit, designed specifically for the reduction of audible noise in virtually any audio source. Noise reduction is the process of removing noise from a signal.

PROJECT OUTPUT

Contact:  

Prof. Roshan P. Helonde

Mobile / WhatsApp:+91-7276355704

Email: roshanphelonde@rediffmail.com

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An Implementation of Palm Print Recognition System Using Gabor Filter Full Matlab Project

ABSTRACT

                   Palm  print  authentication  is  one  of  the  modern  bio-metric techniques, which employs the vein pattern  in  the  human palm  to  verify  the  person.  The merits  of  palm  vein  on classical  bio-metric  (e.g.  fingerprint,  iris,  face)  are  a  low risk  of  falsification,  difficulty  of  duplicated  and  stability. In  this  Project,  a  new  method  is  proposed  for  personal verification  based  on  palm  Print  features.  In  the propose method,  the  palm  vein  images  are  firstly  enhanced  and then  the  features  are extracted  by  using  bank  of  Gabor filters. Bio-metric   technology   refers   to   a pattern   recognition system  which  depends  on  physical  or  behavioral  features for the  person  identification.

PROJECT OUTPUT

Contact:  

Prof. Roshan P. Helonde

Mobile / WhatsApp:+91-7276355704

Email: roshanphelonde@rediffmail.com

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Region of Interest (ROI) Based Image Compression Full Matlab Project Code

ABSTRACT
                  The main goal of region of interest (ROI) based Image compression is to enhance the compression efficiency for transmission and storage.Thus, the ROI area is compressed with lossles compression scheme and the background with the lossy compression scheme

Algorithm Steps

    Initialize the parameters of an image and load the original image to be compressed.
    Select ROI
    Create Mask
    Seperate BG in another image.
    Encoding of ROI region is performed selectively with JPEG with lossless scheme
    Encoding of BG region is performed selectively with JPEG with Lossy Scheme
    Merge the ROI and BG.
    After reconstruction, the image is correlated with original image.
    Evaluate the result using parameters like PSNR and MSE.
 

 PROJECT OUTPUT

Contact:  

Mr. Roshan P. Helonde

Mobile / WhatsApp:+917276355704

Email: roshanphelonde@rediffmail.com

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