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ABSTRACT: Remote sensing images (ranges from satellite to seismic) are affected by number of noises likeinterference, impulse and speckle noises. Image denoising is one of the traditional problems in digitalimage processing, which plays vital role as a pre-processing step in number of image and videoapplications. Image denoising still remains a challenging research area for researchers because noiseremoval introduces artifacts and causes blurring of the images. This study is done with the intension ofdesigning a best algorithm for impulsive noise reduction in an industrial environment. A review of thetypical impulsive noise reduction systems which are based on order statistics are done and particularizedfor the described situation. Finally, computational aspects are analyzed in terms of PSNR values andsome solutions are proposed.
Signal & Image Processing. 01/2011;
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ABSTRACT: Multiprocessor task scheduling is an important and computationally difficult problem. This paper proposes a comparison study of genetic algorithm and list scheduling algorithm. Both algorithms are naturally parallelizable but have heavy data dependencies. Based on experimental results, this paper presents a detailed analysis of the scalability, advantages and disadvantages of each algorithm. Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uni-processor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given task should execute. In multiprocessor systems, an efficient scheduling of a parallel program onto the processors that minimizes the entire execution time is vital for achieving a high performance. This scheduling problem is known to be NP- Hard. In multiprocessor scheduling problem, a given program is to be scheduled in a given multiprocessor system such that the program's execution time is minimized. The last job must be completed as early as possible. Genetic algorithm (GA) is one of the widely used techniques for constrained optimization. Genetic algorithms are basically search algorithms based on the mechanics of natural selection and natural genetics. List scheduling techniques assign a priority to each task to be scheduled then sort the list of tasks in decreasing priority. As processors become available, the highest priority task in the task list is assigned to be processed and removed from the list. If more than one task has the same priority, selection from among the candidate tasks is typically random. This paper compares Genetic algorithm (GA) with List Scheduling heuristic (LSH) to solve scheduling problem of multiprocessors.
International Journal of Computer Science Issues. 01/2010;
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ABSTRACT: Biometric authentication technology is gaining much importance as it serves as a powerful alternative for traditional password based authentication. In the current scenario securing the biometric template against attack is an important issue. Fuzzy vault is a proven biometric crypto system that is used to protect biometric templates and secret data. Multi biometric systems are more secure compared to their single biometric counterparts. In this work, fuzzy vault framework is used to secure both retina and iris template. Retina and iris can be used in high security applications like access control, military applications, border security control. The proposed multimodal fuzzy vault is constructed with feature points extracted from retina and iris. Combination of retina and iris enhances the user convenience as they can be captured from the user by the same device. This work measures the security of the resultant vault by using min-entropy.
International Journal of Computer Applications. 01/2010;
