In this paper, real-coded genetic algorithm (GA) is used for designing two-channel quadrature mirror filter (QMF) banks based on the Kaiser Window. The shape of the Kaiser window and the cutoff frequency of the prototype filter are optimized using a simple GA. The optimized QMF banks are exploited as mother wavelets for speech compression based on discret wavelet transform (DWT). The simulation results show the efficiency of the GA for designing QMF banks using adjustable windows length and especially for optimizing wavelet filters used in speech compression based on wavelets. In addition, a comparative of performance of the developed wavelets filters using GA and others known wavelets is made in term of objective criteria (CR, SNR, PSNR, and NRMSE). The simulation results show that the optimized wavelets filters outperform others wavelets already exist used for speech compression.

Image mosaic is to be combine several views of a scene in to single wide angle view. This paper proposes the feature based image mosaic approach. The mosaic image system includes feature point detection, feature point descriptor extraction and matching. A RANSAC algorithm is applied to eliminate number of mismatches and obtain transformation matrix between the images. The input image is transformed with the correct mapping model for image stitching and same is estimated. In this paper, feature points are detected using steerable filters and Harris, and compared with traditional Harris, KLT, and FAST corner detectors.

Lung cancer is distinguished by presenting one of the highest incidences and one of the highest rates of mortality among all other types of cancers. Detecting and curing the disease in the early stages provides the patients with a high chance of survival. 
This work aims at detecting lung nodules automatically through computerized tomography (CT) image. Accordingly, this article aim at presenting a method to improve the efficiency of the lung cancer diagnosis system, through proposing a region growing segmentation method to segment CT scan lung images. Afterwards, cancer recognition are presenting by Fuzzy Inference System (FIS) for differentiating between malignant, benign and advanced lung nodules. In the following, this paper is testing the diagnostic performances of FIS system by using artificial neural networks (ANNs). Our experiments show that the average sensitivity of the proposed method is 95%.

In this paper, we propose a new steganography technique using the snake scan ordering strategy. The proposed method hides the secret data that is an image in another image, known as the cover image. In this method, the pixel values of the secret image are organized in snake scan order, which are preprocessed to reduce their size. The resultant data is embedded into the Least Significant Bits (LSBs) of the pixels of the cover image. To minimize the error/distortion, the pixel values of the stegoimage are adjusted using Optimal Pixel Adjustment Process (OPAP). The performance of the proposed method is compared with that of the simple LSB substitution method, Chang et al. method, Thein & Lin method, and Chen method in terms of Peak Signal to Noise Ratio (PSNR). Our proposed method has higher PSNR in almost all cases.

Certain aspects of balance control can be affected by some entries as vision, proprioception, direction, age, Gender, height and weight. The knowledge of the effects of these factors on postural equilibrium allows differentiating pathological and physiological postural aspects. The aim of this study is to define the effects of these entries on postural control by analyzing the parameters: mean velocity of CoP (center of pressure), RMS (root mean square) CoP of displacement, Range of COP, CEA (confidence ellipse area). We examined healthy subjects between 19-42 years of age during the quiet stance under static conditions: keeping foot outspread and opened eyes (PE_YO), tighten foot and opened eyes (PS_YO), outspread foot and closed eyes (PE_YF), tightened foot and closed eyes (PS_YF). 
Experimental results through all studied parameters permit to conclude that the lack of vision and the situation with tighten foot cause a degradation of balance maintaining. They indicate also that it is easier to maintain equilibrium on the anteroposterior direction than mediolateral direction. Results show also a less well-controlled posture for male related to female.
Results display also that the postural parameters studied failed to find significant effect of the height, weight and age on the postural stability.

In this paper we represent Security application which is developed using concepts of Video Analytics. User can draw Trip wire on video stream with help of Mouse Callback events. Using this application user can restrict any area of total video scene. Direction selection for tripping is also a choice of a user. If any undesired moving object cross this drawn trip wire then motion of this moving object is getting detected and also tracked. If object crosses trip wire in the same direction as that of user selected then Alarm Indication will appear on that moving object. OpenCV library functions are used for motion detection and motion tracking. CAMShift algorithm is implemented for tracking. An experimental result shows Motion detection, Motion Tracking and drawn trip wire on video.

Visual cryptography is considered to be a vital technique for hiding visual data from intruders. Because of its importance, it finds applications in various sectors such as E-voting system, financial documents and copyright protections etc. A number of methods have been proposed in past for encrypting color images such as color decomposition, contrast manipulation, polynomial method, using the difference in color intensity values in a color image etc. The major flaws with most of the earlier proposed methods is the complexity encountered during the implementation of the methods on a wide scale basis, the problem of random pixilation and insertion of noise in encrypted images. This paper presents a simple and highly resistant algorithm for visual cryptography to be performed on color images. The main advantage of the proposed cryptographic algorithm is the robustness and low computational cost with structure simplicity. The proposed algorithm outperformed the conventional methods when tested over sample images proven using key analysis, SSIM and histogram analysis tests. In addition, the proposed method overshadows the standard method in terms of the signal to noise ratio obtained for the encrypted image, which is much better than the SNR value obtained using the standard method. The paper also makes a worst case analysis for the SNR values for both the methods.

This paper gives the survey of the existing developments of Visual object target tracking using particle filter from the last decade and discusses the advantage and disadvantages of various particle filters. A variety of different approaches and algorithms have been proposed in literature. At present most of the work in Visual Object Target Tracking is focusing on using particle filter. The particle filters has the advantage that they deal with nonlinear models and non-Gaussian innovations, and they focus sequentially on the higher density regions of the state space, mostly parallelizable and easy to implement, so it gives a robust tracking framework, as it models the uncertainty and showing good improvement in the recognition performance compared to the kalman filter and other filters like Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF).Various features and classifiers that are used with particle filter are given in this survey.