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{"references": ["S. Banks, Signal Processing, Image Processing and Pattern\nRecognition, Prentice Hall International, 1995.", "A.Harjoko, S.Hartati,, A Defect Detection Method for Quality Control in\nCeramic Tile Industry, Proceedings The First Jogja Regional Physics\nConference, Section E Geophysics and Applied Physics., Yogyakarta,\n2004.", "E .Hassanien, A. Badr, A Comparative Study on Digital, Enhancement\nAlgorithm Based on Fuzzy Theory, Studies in Informatics and Control,\nVol 12, No.1, 2003.", "S.Haykin, Neural Network: A Comprehensive Foundation. New Jersey:\nPrentice \u00d4\u00c7\u00f6Hall, 1999.", "P. Gonzales, Digital Image Processing, Addison-Wesley, New York,\n1990.", "F.O,Karray, C.Silva, Soft Computing and Intelligent Systems Design\nTheory, Tools and Applications , Pearson Addison Wisley, 2004.", "J.R. Jang, C.T Sun., Neuro-Fuzzy and Soft Computing a Computational\nApproach to Learning and Machine Intelligence, Prentice Hall, Inc.,\nNew Jersey, 1997.", "HR. Tizhoosh, M. Fochem, Image Enhancement with Fuzzy Histogram\nHyperbolization, Proceeding of EUFIT-95, vol.3, 1695-1698, 1995."]}
A prototype of an anomaly detection system was developed to automate process of recognizing an anomaly of roentgen image by utilizing fuzzy histogram hyperbolization image enhancement and back propagation artificial neural network. The system consists of image acquisition, pre-processor, feature extractor, response selector and output. Fuzzy Histogram Hyperbolization is chosen to improve the quality of the roentgen image. The fuzzy histogram hyperbolization steps consist of fuzzyfication, modification of values of membership functions and defuzzyfication. Image features are extracted after the the quality of the image is improved. The extracted image features are input to the artificial neural network for detecting anomaly. The number of nodes in the proposed ANN layers was made small. Experimental results indicate that the fuzzy histogram hyperbolization method can be used to improve the quality of the image. The system is capable to detect the anomaly in the roentgen image.
Image processing, anomaly detection., artificial neural network
Image processing, anomaly detection., artificial neural network
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