A Comparative Experiment of Several Shape Methods in Recognizing Plants

Computer Science – Computer Vision and Pattern Recognition

Scientific paper

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8 pages; International Journal of Computer Science & Information Technology (IJCSIT), Vol 3, No 3, June 2011

Scientific paper

10.5121/ijcsit.2011.3318

Shape is an important aspects in recognizing plants. Several approaches have been introduced to identify objects, including plants. Combination of geometric features such as aspect ratio, compactness, and dispersion, or moments such as moment invariants were usually used toidentify plants. In this research, a comparative experiment of 4 methods to identify plants using shape features was accomplished. Two approaches have never been used in plants identification yet, Zernike moments and Polar Fourier Transform (PFT), were incorporated. The experimental comparison was done on 52 kinds of plants with various shapes. The result, PFT gave best performance with 64% in accuracy and outperformed the other methods.

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