Applied Mechanics and Materials Vol. 573

Abstract: Cognitive Radio Networks (CRNs) have been proposed to increase the efficiency of channel utilization; presently the demand for wireless bandwidth is increased. Cognitive Radio Network can enable the sharing of channels among unlicensed and licensed users on a non-interference basis. An unlicensed user (i.e., secondary user) should monitor for the presence of a licensed user (i.e., primary user) to avoid interfering with a primary user. However to get more gain, an attacker also called self-ish secondary user may copy a primary user’s signal to cheat other secondary users. Therefore a primary user detection method is needed to detect the difference between a primary user’s signal and secondary user’s signal. In this paper, unsupervised learning methods such as K-means and SOM techniques are used to classify the signals and also measure the performance parameters such as throughput, end-to-end delay, energy consumption, packet delivery ratio and collision rate of the channel.

Abstract: Fingerprints are graphical ridge and valley patterns on the tips of human fingers. Owing to their uniqueness and permanence, the use of fingerprints is considered to be one of the most reliable methods of personal verification. Fingerprints are today among the most popularly used biometric modalities in automatic verification systems. At the same time, Protecting the privacy of Fingerprint is an important one, here a novel system propose protecting fingerprint by combining two different fingerprints. In the enrolment stage, fingerprints will be captured from two different fingers. Minutiae positions are extracted from one fingerprint (its the detailed pattern of the fingerprint). The orientation, (it indicates the flow of ridges and valleys) from other fingerprint, and the reference points are calculated from both the two fingerprints. Extracted combined minutiae templates are stored into database. Here A Delaunay Triangulation indexing scheme has been designed for protecting biometric template and non-invertible template are calculated for verifies the authorized person. By using the Delaunay triangulation method fingerprint privacy has to be improved.

Abstract: In recent years, the 3-D face has become biometric modal, for security applications. Dealing with occlusions covering the facial surface is difficult to handle. Occlusion means blocking of face images by objects such as sun glasses, kerchiefs, hands, hair and so on. Occlusions are occurred by facial expressions, poses also. Basically consider two things: i) Occlusion handling for surface registration and ii). Missing data handling for classification. For registration to use an adaptively-selected-model based registration scheme is used. After registering occlusions are detected and removed. In order to handle the missing data we use a masking strategy call masked projection technique called Fisher faces Projection. Registration based on the adaptively selected model together with the masked analysis offer an occlusion robust face recognition system.

Abstract: . Image search engines (e.g. Google Image Search, Bing Image Search) mostly depends on the given query surrounding text features. It increases complexity to interpret users search intention only by giving single query keywords and this leads to ambiguous and noisy search results. To solve the ambiguity in the image search, consider visual information along with the text features. In this approach user has to click a single search return image and the search results are re-ranked based on the similarity in visual and textual content. Our work is to capture user search intention by doing one-click image search has four steps. Adaptive weight categories are predefined to category the query image and this helps to re-rank the text based search results. Keywords are expanded based on the selected query image visual content that helps to capture user intention. Based on the expanded keywords image pool get expanded that contain more relevant images with the query image. Expanded keywords are also used to expand the query image that lead to multiple positive similar images and the similarity metrics are learned for page re-ranking. Re-ranking of similarity images to the query image based on photo quality assessment to provide better search results.

Abstract: In the arrival of today’s highly integrated multimedia device and fast emerging applications, image processing have become more important than any others. These devices require complex image processing tasks lead to a very challenge design process as it demands more efficient and high processing systems. The scope of the project is to extract locations and features of multi objects in an image for object recognition. For low power consumption and better performance we design a proposed system in FPGA. In existing system an cell based multi object feature extraction algorithm is used to extract simultaneously autocorrelation feature of objects. It is calculated using zeroth order and first order moments to obtain the size and location of multiple objects. To reduce computational complexity and memory consumption, Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) is used to extract the feature of multiple objects are proposed. In the local binary pattern, the LBP value is computed by comparing a gray level value of centre pixel in an image with its neighbors. The local ternary pattern is extended from LBP to three-valued code in which gray values are quantized to zero,+1,-1. The proposed architecture is designed using verilog HDL, simulated using Modelsim software and synthesized using Xilinx project navigator.

Abstract: This paper proposes a robust algorithm for the quality improvement in human silhouettes, to improve the gait recognition percentage of a person. In silhouette based gait recognition approach, the presence of incomplete and noisy silhouettes has a direct impact on recognition performance. Using blob detection, initially the incomplete silhouettes are identified. Fusion of frame difference energy image with dominant energy image of a silhouette along with a morphological filter output, preserve the kinetic and kinematic information to make incomplete silhouette into a high quality and a complete silhouette. The results prove that the resultant silhouettes are well suited for human gait recognition algorithm with improved variance. The silhouette database is taken from CASIA database. (Institute of Automation, Chinese Academy of Sciences).

Abstract: Biometrics authentication is playing a vital role in providing security and privacy. This paper presents a contemporary approach for identifying an individual using unimodal biometrics. Finger vein based authentication system is a promising technology and now-a-days widely used because of its important features such as resistant to criminal tampering, high accuracy, ease of feature extraction and greater authentication speed. The feature vein patterns extracted by Contourlet transform decompose into directional sub bands in different orientations at various scales. The Support Vector Machine (SVM) classifier is used for pattern matching. Thus the experimental results shows that our proposed method tested on two different databases of finger vein images improves recognition rate with high matching speed.

Abstract: Breast cancer has been increasing over the past three decades. Early detection of breast cancer is crucial for an effective treatment. Mammography is used for early detection and screening. Especially for young women, mammography procedures may not be very comfortable. Ultrasound has been one of the most powerful techniques for imaging organs and soft tissue structure in the human body. It has been used for breast cancer detection because of its non-invasive, sensitive to dense breast, low positive rate and cheap cost. But due to the nature of ultrasound image, the image suffers from poor quality caused by speckle noise. These make the automatic segmentation and classification of interested lesion difficult. One of the frequently used segmentation method is active contour. If this initial contour of active contour method is selected outside the region of interest, final segmentation and classification would be definitely incorrect. So, mostly the initial contour is manually selected in order to avoid incorrect segmentation and classification. Here implementing a method which was able to locate the initial contour automatically within the multiple lesion regions by using the wavelet soft threshold speckle reduction method, statistical features of the lesion regions and neural network and also we are able to automatically segment the lesion regions properly. This will help the radiologist to identify the lesion boundary automatically.

Abstract: The Wavelet Transform is a multi-resolution transform, that is, it allows a form of time–frequency analysis (or translation–scale in wavelet speak). When using the Fourier transform the result is a very precise analysis of the frequencies contained in the signal, but no information on when those frequencies occurred. The wavelet based image compression algorithms are used widely compared with other conventional compression algorithms. The wavelet coding based on the coefficient selection and sub band level. In this paper we have used two wavelets such as spherical and geometric wavelets. The spherical representation is a hierarchical description of how total energy gets distributed within each wavelet sub band.In the proposed method, we used fuzzy quantization technique for coefficient selection in the spherical wavelet. The other scheme introduces binary space partitioning scheme and geometric wavelet, where the existing pruning method of binary space partitioning is replaced by the genetic algorithm. We had another experiment with geometric wavelet with Artificial Bee Colony (ABC) algorithm. The experimental results for all the three methods are discussed in this paper. The advantages of these methods are the improved PSNR values at high and medium bit rates.

Abstract: The widespread operation of modified algorithm (National Institution of Standard Technology Fingerprint image Quality (NIFQ)) in government applications allow some persons with illegal environment by neglecting the detection of altered fingerprints. By using the fingerprint quality assessment software, it is difficult to find the altered fingerprints, since the quality of image does not degrade. This paper focuses on optimizing the modified NFIQ algorithm by implementing particle swarm optimization (PSO) based on a fingerprint identification system. It can also be helpful in improving the performance by accuracy and robustness for detecting the fingerprint which is altered.