Morphological pattern spectrum is a useful shape description tool for quantifying the geometric shape feature of both binary and gray images. In this paper, a general frame of pattern spectrum is developed for both continuous-scale and discrete-scale based on the efficient and reduced redundancy multiscale image representation. A discussion for the basic properties of generalized pattern spectrum is presented in the paper. Algorithms for shape recognition and shape classification using continuous and discrete-scale pattern of images are proposed in Euclidian space.
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