SHAPE-DESCRIPTION AND RECOGNITION USING THE HIGH-ORDER MORPHOLOGICAL PATTERN SPECTRUM

Shape analysis and recognition is an important issue in modern image processing and computer vision. It needs to solve three problems: possibility, sensitivity and robustness. To deal with the third one, this paper proposes the high order morphological pattern (HP) spectrum which relies upon the difference between two different sized alternating sequential morphological transformations on the original image. The HP spectrum is characterized by the translating invariance and rotating invariance for the isotropic; structuring element. It is also proved that the higher order components of HP spectrum for a noisy image are exactly identical to these for the noise-free image under certain conditions. Also, the results of the experiments conducted, have shown that the HP spectrum shows the strongest robustness in a noisy environment.