Image Enhancement Using MamdaniFuzzy Inference System
Praveen K Shetty , Dr.V.S.Veena Devi
Abstract
—Image enhancement means to improve the quality of the images for better human perception. The impulsive noise can be reduced and also by using different image enhancement techniques edges of the images can be sharpened. The quality of the original image is increased for better analysis by a human or a machine by using image enhancement technique. One of the image enhancement techniques is fuzzy image enhancement. Fuzzy logic deals with studying of possibiliticlogic or several valued logic, it uses approximation rather than fixed and exact reasoning. It handles partial truth, where the truth values may either be in between of completely true values or completely false value. Fuzzy image processing is considered important application areas of fuzzy domain. The purpose here is to increase the contrast of the original image using triangular membership function and fuzzy rules from Mamdani fuzzy inference system. Edge detection of the original image is done and by using triangular membership function image is converted to fuzzy plane from pixel plane. Fuzzy rules are applied on the original image and defuzzification is done on the same to get the enhanced image. For enhanced image Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) has been calculated. The implementation work will be done using MATLAB 7.5 image processing tool box.
Fuzzy set, Mamdani fuzzy inference system, Membership function, Fuzzy if then rules.
[1] TarunMahashwari, Amit Asthana, “Image Enhancement Using Fuzzy Technique”, International Journal Of Research Review In Engineering Science & Technology (ISSN 2278–6643) Volume-2, Issue-2, June-2013 IJRREST. Pp. 1-4
[2] Gonzalez R. C. and Woods R. E., Digital Image Processing, 3'd ed.Upper Saddle River, NJ: Prentice- Hall, 2006.
[3]Yanxia Wang, QiuqiRuan, “An Improved UnsharpMasking method for Palmprint Image Enhancement”, Proceedings of the First International Conference on Innovative Computing, Information and Control (ICICIC'06), 2006 IEEE.
[4]Timothy j.Ross, Fuzzy Logic with Engineering Applications, 2’d edition
[5] SasiGopalan, Madhu S Nair, and Souriar Sebastian Approximation Studies on “Image Enhancement Using Fuzzy Technique”International Journal of Advanced Science and Technology Vol. 10, September, 2009, pp. 11-26.
[6] Reshmalakshmi C, Sasikumar M, “Image Contrast Enhancement using Fuzzy Technique” ,2013 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2013], IEEE, pp. 861-865.
[7] Zhou Z, “Cognition and removal of impulse noise with uncertainty”. IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 21, NO. 7, JULY 2012, pp. 3157-3167.
[8] Hamid R. Tizhoosh, Bernd Michaelis, “Image Enhancement Based on Fuzzy Aggregation techniques”, IEEE IMTC'99,vol. 3, 1999 IEEE, pp. 1813-1817.
[9] Dr.G.Sudhavani, M.Srilakshmi, S. Sravani, P. Venkateswara Rao K Enhancement of Low Contrast Images Using Fuzzy Techniques SPACES-2015, Dept of ECE, K L university. pp. 286-290.
[10] NutanY.Suple, Sudhir M. Kharad, “Basic approach to image contrast enhancement with fuzzy inferencesystem”, International Journal of Scientific and Research Publications, Volume 3, Issue 6, June 2013, pp. 1-4.
[Praveen K Shetty, Dr.V.S.Veena Devi (2015), Image Enhancement Using MamdaniFuzzy Inference System, International Journal of Innovative Research in Computer Science & Technology (IJIRCST), Vol-3, Issue-4, Page No-37-43], (ISSN 2347 - 5552). www.ijircst.org
Praveen K Shetty
Student, M.Tech (DECS), Department of E & C Engineering, St Joseph Engineering College, Mangaluru, D.K
