This paper presents one novel algorithm for minimization of non-zero coefficients of Finite Impulse response (FIR) pulse-shaping filter, mostly employed in practical digital communication system to alleviate the difficulties resulting from Inter Symbol Interference (ISI), followed by its hardware optimization on a Field Programmable Gate Array (FPGA) chip . Filter performance has been demonstrated through the inclusion of impulse response, magnitude spectrum and requirement of various hardware blocks. The supremacy of our algorithm has been substantiated by comparing its performance with other existing models of different length. From the simulation results, it has been concluded that the proposed FIR filter provides a considerable reduction in the number of non-zero coefficients without affecting its performance significantly.

Diabetic retinopathy is a severe and widely spread eye disease. Early diagnosis and timely treatment of these clinical signs such as hard exudates could efficiently prevent blindness. The presence of exudates within the macular region is a main hallmark of diabetic macular edema and allows its detection with high sensitivity. In this paper, we combine the k-means clustering algorithm and mathematical morphology to detect hard exudates (HEs) in retinal images of several diabetic patients. This method is tested on a set of 50 ophthalmologic images with variable brightness, color, and forms of HEs. The algorithm obtained a sensitivity of 95.92%, predictive value of 92.28% and accuracy of 99.70% using a lesion-based criterion.

As a rule, a video signal has high temporal redundancies due to the high correlation between successive frames. This redundancy has not been deflated enough by current video compression techniques. In this paper, we present a new video compression technique which tends to hard exploit the relevant temporal redundancy in the video to improve solidity efficiency with minimum processing complexity. It includes 3D (Three Dimension) to 2D (Three Dimension) transformation of the video that allows exploring the temporal redundancy of the video using 2D transforms and avoiding the computationally demanding motion recompense step. This transformation converts the spatial and temporal correlation of the video signal into a high spatial correlation. Indeed, this technique transforms each group of pictures into one picture eventually with high spatial correlation. SPIHT (Set Partitioning in Hierarchical Trees) exploits the properties of the wavelet-transformed images to increase its efficiency. Thus, the De-correlation of the resulting pictures by the DWT (Discrete Wavelet Transform) makes efficient energy compaction, and therefore produces a high video compression ratio. Many experimental tests had been conducted to prove the technique efficiency especially in high bit rate and with slow motion video.

In this paper, an efficient and accurate method for human color skin recognition in color images with different light intensity will proposed .first we transform inputted color image from RGB color space to YCBCR color space and then accurate and appropriate decision on that if it is in human color skin or not will be adopted according to YCBCR color space using fuzzy, adaptive fuzzy neural network(anfis) methods for each pixel of that image. In our proposed system adaptive fuzzy neural network(anfis) has less error and system worked more accurate and appropriative than prior methods.

There is a serious flaw in existing image search engines, since they basically work under the influence of keywords. Retrieving images based on the keywords is not only inappropriate, but also time consuming. Content Based Image Retrieval (CBIR) is still a research area, which aims to retrieve images based on the content of the query image. In this paper we have proposed a CBIR based image retrieval system, which analyses innate properties of an image such as, the color, texture and the entropy factor, for efficient and meaningful image retrieval. The initial step is to retrieve images based on the color combination of the query image, which is followed by the texture based retrieval and finally, based on the entropy of the images, the results are filtered. The proposed system results in retrieving the images from the database which are similar to the query image. Entropy based image retrieval proved to be quite useful in filtering the irrelevant images thereby improving the efficiency of the system.

Visual information is very much important for human to perceive, recognize and understand the surrounding world. As we live in the age of multimedia video sequences are very useful to us for providing information. Video involves a huge amount of data. So video compression is necessary Motion compensation has lot of computation in total video compression process. Fast motion vector estimation is a key-factor in video coding standard. Full search algorithm is the best algorithm between all the block matching algorithms to estimate the motion vector estimation with a huge computation cost. The challenge is to reduce the computational complexity of Full Search algorithm without losing too much quality at the output.
In this paper we propose to implement the fuzzy logic based Four Step Search algorithm which performs better than other block matching algorithms.

Organ segmentation is an important step in various medical image applications. Accurate spleen segmentation in abdominal CT images is one of the most important steps for computer aided spleen pathology diagnosis. In this paper, we have proposed a new semi-automatic algorithm for spleen area extraction in abdominal CT images. The algorithm contains several stages. A spleen segmentation method is based on watershed approach. The first, we seek to determine the region of interest by applying the morphological filters such as the geodesic reconstruction to extract the spleen. Secondly, a pre-processing method is employed. In this step, we propose a method for improving the image gradient by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the spleen segmentation by the watershed transform controlled by markers. The new segmentation technique has been evaluated on different CT images, by comparing the semi-automatically detected spleen contour to the spleen boundaries manually traced by an expert. The experimental results are described in the last part in this work. The automated method provides a sensitivity of 95% with specificity of 99% and performs better than other related methods.