iosr-JCE   Volume-16 ~ Issue-5 ~ Sep-Oct 2014

Abstract: Ant Colony System (ACS) is competitive with other nature-inspired algorithms on some relatively simple problems. This project proposes an ant colony optimization algorithm for tuning generalization of fuzzy rule. The use of Ant Colony Optimization (ACO) for classification is investigated in depth, with the development of the AntMiner+ algorithm. AntMiner+ builds rule based classifiers, with a focus on the predictive accuracy and comprehensibility of the final models. The key differences between the proposed AntMiner+ and previous AntMiner versions are the usage of the better performing MAX-MIN ant system, a clearly defined and augmented environment for the ants to walk through, with the inclusion of the class variable to handle multi-class problems, and the ability to include interval rules in the rule list. Ant system is a general purpose algorithm inspired by the study of behavior of ant colonies. It is based on cooperative search paradigm that is applicable to the solution of combinatorial optimization problem. The institutions concern the routing network studies the application of data mining techniques for network traffic risk analysis. The proposed work aims at spatial feature of the traffic load and demand requirements and their interaction with the geo routing environment. In previous work, the system has implemented some spatial data mining methods such as generalization and characterization. The proposal of this work uses intelligent ant agent to evaluate the search space of the network traffic risk analysis along with usage of genetic algorithm for risk pattern.

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Abstract : Plastic surgery provide a way to enhance the facial appearance. The non-linear variations introduced by the plastic surgery has raised a challenge for face recognition algorithms. In this research we match the face image before and after the plastic surgery. First generate non-disjoint face granules at multiple levels of granularity. The feature extractors are used to extract features from the face granules. The features are then processed by using principal component analysis (PCA) algorithm. Evaluate the weighted distance and match the pre and post surgery images based on weighted distance. The proposed system yield high identification accuracy and take less time for recognition as compared to the existing system.

Keywords: Plastic surgery;face recognition;Granular Computing;PCA Algorithm

[1]. H. S. Bhatt, S. Bharadwaj, R. Singh, and M. Vatsa, "Recognizing surgically altered face images using multi-objective evolutionary algorithm" in Proc. Int. Conf. Biometrics:Theory Applications and Systems, 2013
[2]. G. Aggarwal, S. Biswas, P. J. Flynn, and K. W. Bowyer, "A sparse representation approach to face matching across plastic surgery," in Proc.Workshop on the Applications of Computer Vision, 2012, pp. 1–7.
[3]. M. De Marsico, M. Nappi, D. Riccio, and H. Wechsler, "Robust face recognition after plastic surgery using local region analysis," in Proc. Int. Conf. Image Analysis and Recognition, 2011, vol. 6754, pp. 191–200.
[4]. H. S. Bhatt, S. Bharadwaj, R. Singh, and M. Vatsa, "On matching sketches with digital face images," in Proc. Int. Conf. Biometrics:Theory Applications and Systems, 2010, pp. 1–7.
[5]. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol. 60, no. 2, pp. 91–110, 2004.

Abstract : Reducing noise from the various images like Real images, medical images and satellite images etc. is a challenging task in digital image processing. Noises are removed as pre processing which are needed for image enhancement, restoration, compression, registration, analysis as well as feature extraction and texture analysis. Several approaches are there for noise reduction. The proposed filtering technique in this paper removes speckle noise from the real images effectively. Quantitative analysis is done by various measures like Noise Variance, Mean Square Error, Noise Mean Value, Noise Standard Deviation, Equivalent Number of Looks (ENL) and PSNR and the results exhibit the performance of the proposed filter.

Keywords: ENL, frost filter, lee filter, PSNR, Speckle noise, speckle filters

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