Digital Processing

Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set of blur invariants using the orthogonal Legendre moments. Some important properties of Legendre moments for the blurred image are presented and proved. The performance of the proposed descriptors is evaluated with various point-spread functions and different image noises. The comparison of the present approach with previous methods in terms of pattern recognition accuracy is also provided. Theexperimental results show that the proposed descriptors are more robust to noise and have better discriminative power than the methods based on geometric or complex moments.

The proposed concept of Fpga based design and Implementation of image Architecture Using Xilinx System generator. Recent advances in synthesis tools for SIMULINK suggest a feasible high-level approach to algorithm implementation for embedded DSP systems. An efficient FPGA based hardware design for enhancement of color and grey scale images in image and video processing. The top model – based visual development process of SIMULINK facilitates host side simulation and validation, as well as synthesis of target specific code, furthermore, legacy code written in MATLAB or ANCI C can be reuse in custom blocks. However, the code generated for DSP platforms is often not very efficient. We are implemented the Image processing applications on FPGA it can be easily design.

Image fusion is a technique to improve the image quality. In this paper a new way is drawn to fuse two images by using max-min operations in Sugeno’s Intuitionistic fuzzy generator. It operates on image with lot of uncertainties. Firstly input images are reform into Intuitionistic fuzzy images (IFIs) and then evaluate fuzzy rules by using best entropy of input images, and IFIs are reconstructing based on black-count & white-count. This paper compares the performance of Average, Fuzzy Sets, Intuitionistic Fuzzy Sets and Sugeno’s type Intuitionistic fuzzy (proposed method) in terms of various performance measures.

Character recognition, usually abbreviated to optical character recognition or shortened OCR, is the mechanical or electronic translation of images of handwritten, typewritten or printed text (usually captured by a scanner) into machine-editable text. It is a field of research in pattern recognition, artificial intelligence and machine vision. Though academic research in the field continues, the on character recognition has For many document-input tasks, character recognition is the most cost-effective and speedy method available. And each year, the technology frees acres of storage space once given over to file cabinets and boxes full of paper documents. The objective of this paper is to identify handwritten characters with the use of neural networks. We have to construct suitable neural network and train it properly. The program should be able to extract the characters one by one and map the target output for training purpose. After automatic processing of the image, the training dataset has to be used to train “classification engine” for recognition purpose. The program code has to be written in MATLAB and supported with the usage of Graphical User Interface (GUI).

Kidney stone disease is very common among Indians and approximately 5-7 million patients suffer from stone disease.The most popular imaging modality for its treatment is ultrasound imaging.Segmentation accuracy determines the eventual success or failure of computerized analysis procedures. Traditional methods available for segmentation of kidney stones are not accurate. We use the evolutionary techniques for segmentation of the kidney stone ultrasound images for the first time based on electromagnetism optimization algorithm and harmony search algorithm for determining multilevel threshold of images. In most cases, the optimal thresholds are found by the minimizing or maximizing an objective function, which depends on the positions of the thresholds. We identify a class of objective functions for which the optimal thresholds can be found using algorithms with low time complexities. The Kapur’s entropy function and Otsu’s between class variance is maximized using these algorithms and an optimal threshold values at different levels are found out. The area of extracted stone is calculated and compared with the area given by the expert radiologist. The other metric used to compare the segmented image and the original image is the peak signal to-noise-ratio (PSNR) value. The relative error is also calculated to show the segmentation accuracy of each method.

Fast and robust analysis of hand gestures has received increasingly more attention in the last two decades. Sign language forms a major communication channel among the deaf people. Although they successfully communicate with each other when using sign language, they face many difficulties when they try to communicate with hearers, especially those who are unfamiliar with the sign language. In this paper we have designed a frame work for analyzing and recognizing the sign gesture language. The proposed method comes across different steps where image acquisition is done first. After image acquisition, segmentation process is carried out. The segmentation process used is the HSI segmentation. Next the images are made free from noise by performing the noise removal process using median filters. Next step is the feature extraction and recognition. For feature extraction, the feature vectors containing information about the aspect ratio, holes etc are extracted along with the shape features. The proposed method proves to be more efficient in data acquisition using sign gesture.

The digital image processing has been proved to be an effective tool for analysis in various fields and applications in engineering. Among the segmentation methods, image thresholding technique is one of the most well known methods due to its simplicity, robustness, and high precision. In this paper an attempt is made for an efficient segmentation of Natural calamity images by Healthy Bacteria Foraging Optimization Algorithm.

Technologies have advanced rapidly in the field of digital signal processing due to advances made in high speed, low cost digital integrated chips. These technologies have further stimulated ever increasing use of signal representation in digital form for purposes of transmission, measurement, control and storage. Design of digital filters especially adaptive or semi adaptive is the necessity of the hour for SAR applications. The aim of this research work is to design and performance evaluation of 380-400 KHz Bartlett, Blackman and Chebyshev digital semi adaptive filters. For this work XILINX and MATLAB softwares were used for the design. As pert of practical research work these designs were translated using FPGA hardware SPARTAN-3E kit. These were optimized, analyzed, compared and evaluated keeping the sampling frequency at 5 MHz for 64 order. Both these filters designed using software and hardware were tested by passing a sinusoidal test signal of 381 KHz along with noise and the filtered output signals are presented.

Technologies have advanced rapidly in the field of digital signal processing due to advances made in high speed, low cost digital integrated chips. These technologies have further stimulated ever increasing use of signal representation in digital form for purposes of transmission, measurement, control and storage. Design of digital filters especially adaptive or semi adaptive is the necessity of the hour for SAR applications. The aim of this research work is to design and performance evaluation of 380-400 KHz Bartlett, Blackman and Chebyshev digital semi adaptive filters. For this work XILINX and MATLAB softwares were used for the design. As pert of practical research work these designs were translated using FPGA hardware SPARTAN-3E kit. These were optimized, analyzed, compared and evaluated keeping the sampling frequency at 5 MHz for 64 order. Both these filters designed using software and hardware were tested by passing a sinusoidal test signal of 381 KHz along with noise and the filtered output signals are presented.

To speed up the process of detection of tamper in an image it is withheld to segment the image, embed segment with watermark and key as to trace the tamper segment in which key is not found rather than tracing for entire image for tamper detection. Tamper detection algorithm based on superpixel segment level key encryption with svd based watermarking scheme is proposed. This method finds tamper location from watermarked superpixel segments of watermarked image. Secrete key embedded in each segment of watermarked image for finding tamper segment first. If keys not found from any of the segment that segment shows tamper segment of image then find area which is tampered from that segment. To improve the efficiency of the proposed tamper detection against various security attacks such as collage attacks, VQ attacks and content removal attacks. The experimental results shown that proposed tamper detection scheme is shows better performance in terms of efficiency of tamper detection rate higher than 99% in average complex attacks, 100% in common attack and tamper finding speed is 0.02 to 0.04 sec. in various attacks.