Spatial Size Distributions: Applications to Shape and Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A granulometric analysis of specular microscopy images of human corneal endothelia
Computer Vision and Image Understanding
A granulometric analysis of specular microscopy images of human corneal endothelia
Computer Vision and Image Understanding
Morphological texture analysis using optimization of structuring elements
Proceedings of the 11th international conference on Theoretical foundations of computer vision
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
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This paper proposes a novel method of texture analysis based on the mathematical morphology. The pattern spectrum is a mathematical morphological method to describe size distributions of objects contained in an image. Our method is based on the idea to optimize the shape of structuring elements to fit the shape of elementary particles that form a texture. Since the variance of size distribution described by the pattern spectrum is small if the structuring element for calculating the pattern spectrum fits the particles, the shape of elementary object is obtained by the structuring element optimized to reduce the variance of size distribution. Experimental results are shown when the structuring element is restricted to binary ones of 5x5-pixels.