Pattern Recognition in Digital Images using Fractals
Mansoor Farooq1, Mubashir Hassan Khan2
1Mansoor Farooq, Ph.D. Department of Computer Science and Engineering, Shri Venkateshwara University, Kashmir, India.
2Mubashir Hussain Khan, Assistant Professor, Department of Computer Applications, Govt. College for Women M. A., Kashmir, India.
Manuscript received on November 23, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 3180-3183 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B4229129219/2019©BEIESP | DOI: 10.35940/ijeat.B4229.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Pattern recognition in digital images is a conjoint problem with application in remote sensing, electron microscopy, medical imaging and astrophysics, still no general solution which can be rivalled with the human cognitive system in which a pattern can be conceded subject to random positioning and scale. This research has stemmed in the design and implementation of a new algorithm for general pattern recognition based on the use of fractal image compression. This approach has for the first time allowed the pattern recognition problem to be solved in a way that is invariant of rotation and scale. It allows both ANNs and correlation to be used subject to appropriate pre-and post-processing techniques for digital image processing.
Keywords: ANN, Cross-Correlation, Least Square Method, Fractal Image Compression and Pattern Recognition.