B. S. Mousavi
Hatef Higher Education Institute

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Digital image classification by optimised fuzzy system Mehdi Ramezanifard; B. S. Mousavi
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i3.pp1196-1202

Abstract

Image classification is a challenging problem of computer vision. This study reports a fuzzy system to semantic image classification. As it is a complex task, various information of digital image, including: three color space components and two Zernike moments with different order are gathered and utilized as an input of fuzzy inference system to materialize a robust rotation/lighting condition and size invariant image classifier. For better performance, all the membership functions are optimized by genetic algorithm after empirically design stage. 93.07% and 95.25% classification rates empirically design and optimized systems confirm the reliability of proposed method in different image conditions given in this contribution.