Face Recognition with its Various Techniques: A Review
Face recognition is major challenge and provides significant attention of research in the computer vision. In recent years, reliable automated face recognition has become a realistic target of biometrics research. This biometrics will provide identity and verification of the person. The objective of face recognition involves the extraction of different features of the human face from the face image which makes it different from the other persons. In this, we give a review on face recognition system and the various classifications of recognition methods. This paper will also contain the various techniques, like PCA, LDA etc, which are used in the recognition of the face.
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Skin color segmentation in YCBCR color space with fuzzy, anfis
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.
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A multi-agent based control scheme for accelerator pre-injector and transport line for enhancement of accelerator operations
Reliable accelerator operation requires control system with higher level of automation, flexibility, robustness, and optimisation. In this paper a multi-agent system based control scheme is presented for optimal control of accelerator system that improves the plant performance in wide-range of operations. The multi-agent based control schemes for accelerators have been reported in literature. But the scheme proposed in this paper differs significantly form the existing schemes. In this work the agent architecture is formulated based on the control requirements of pre-injector accelerator subsystem (Microtron in particular) and transport line of synchrotron radiation sources. The scheme consists of two software agents at supervisory level that work in an autonomous manner for the optimized control of dynamic system. The Microtron agent architecture augments model assisted adaptive controller for realizing feedback control action at lower layer and goal based logic controller with pre-structure model identifier along with the pattern recognizer at supervisory layer. The TL-1 agent has a model-based, goal-based modular architecture and optimizes the TL-1 control using differential evolution based algorithm. The simulation results of applying this scheme to model of Microtron and Transport Line-1 of INDUS complex shows that this approach is very effective in optimizing the Microtron and TL-1 tuning.
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A Study on the Quality of Central Library Websites of Government Universities in Iran, based on Fuzzy Interface System
This study aimed to assess and rank the quality of central library websites of government universities in Iran based on the fuzzy deduction system. Statistical society includes independent central library websites of government universities in Iran (n=55) that were managed by Ministry of Science, Research and Technology. A survey method research was used for the aim of the study. Moreover, a check list and MATLAB Software were used. Among content criteria, website title was the most important one and among structural criteria, searching in continuous catalogue of the library was the most significant. Classic assessment of findings showed that central library websites of University of Shahed and Sahand University of Technology had the highest quality; on the contrary, central library websites of (Shahid Abbaspour) Power & Water University of Technology and Gorgan University of Agricultural Science and Natural Resources had the lowest quality. Findings of fuzzy deduction system showed that central library website of University of Shahed had the highest quality; however, central library website of (Shahid Abbaspour) Power & Water University of Technology had the lowest quality among other websites. Comparison of classic assessment and fuzzy assessment of central library websites of Iran showed that in an assessment based on the fuzzy deduction system, more precise results are obtained and websites are correctly ranked. In addition, websites can be ranked based on low, medium and high quality. Therefore, it seems that fuzzy deduction system is a better method for assessing and ranking the quality of university library websites. Keywords: Fuzzy Logic; Central Library Website; Applied System, Government Universities, Library Website
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Computing over a multi cloud for MTC applications
IT organizations can now outsource computer hardware by leasing CPU time through cloud computing services. The problem here is the effectiveness is becoming less due to burden on single cloud while working with MTC applications .This paper deals with defining the feasible solutions with MTC applications using the programming models for computing over a Multi clouds instead of single cloud for effectiveness.
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Person Identification using SOM
Security systems are basically based on authentication process. It is being more secure using different approaches. Verity of security systems is available in market but, they uses conventional scheme for identification of a person for an authentication process. Authentication is based on identification process. Recently signals like EEG and ECG called physiological signal of a human is a famous subject for the researcher. Many systems are being developed using this unique human characteristic. It is very hard to copy and universal for every human kind. In experiment for person identification method uses EEG signal, Wavelet Packet Decomposition (WPD) for feature extraction and Self-organizing map (SOM) as a classifier.
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Compacted video based data hiding for motion vectors
There are many researches that have been proposed for embedding data into digital video. However, most of those schemes extending data hiding technique for still images to videos by treating each single frame as a still image and embed data in intra-frame. In this paper, we propose an effective data-hiding scheme that embeds data in digital videos using the phase angle of the motion vector of the macro blocks in the inter-frame. The scheme can be applied to either compressed or uncompressed videos. Furthermore, the embedded data can be extracted directly without using the original video sequences. Our experimental results prove the feasibility of the proposed method. The method is implemented and tested for hiding data in natural sequences of multiple groups of pictures and the results are evaluated. The evaluation is based on two criteria: minimum distortion to the reconstructed video and minimum overhead on the compressed video size. Based on the aforementioned criteria, the proposed method is found to perform well and is compared to a motion vector attribute-based method from the literature.
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Detection of micro-calcifications in mammogram images using probabilistic neural network
This paper presents a novel method for early detection of forming a Tumor i.e. Micro-calcifications in Mammograms. The main objective of this paper is to segment and detect the Micro-calcification (MCCs) from Digital mammograms that helps to provide and support for clinical decision to perform biopsy of the breast. In this paper, there are two aspects. First is to enhance the image by using Mathematical Morphology and denoise by Wavelet Transform and segmentation and detection of Micro-calcifications using Spot detection. Second is to extract texture based features by using Gabor filters from the segmented image and finally classify it by using Probabilistic Neural Network (PNN) classifier. The Mammogram database consist of 154 images, in which 90 images are taken for training the Probabilistic neural network and 64 images are used for testing purpose.
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An Efficient Solution for Implementation of Property Lists in Programming Languages
Supporting different data structures and their variations in both static and dynamic aspects are one of the challenges in programming languages. One of the data structures is property list of which applications use it as a convenient way to store, organize, and access standard types of data. In this paper, the solution methods for implementation Property List as Link List, Hash and Tree are reviewed. Then an efficient way to implement the property list as Set is presented and compared with the existing methods.
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Localization algorithms for wireless sensor networks in recent approaches and future challenges
Recent advances in radio and embedded systems have enabled the proliferation of wireless sensor networks. Wireless sensor networks are tremendously being used in different environments to perform various monitoring tasks such as search, rescue, disaster relief, target tracking and a number of tasks in smart environments. In many such tasks, node localization is inherently one of the system parameters. Node localization is required to report the origin of events, assist group querying of sensors, routing and to answer questions on the network coverage. So, one of the fundamental challenges in wireless sensor network is node localization.
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