Issue No. 05 - September (1988 vol. 10)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.6770
<p>The symbolic representation of gray-value variations is studied, with emphasis on the gradient of the image function. The goal is to relate the results of this analysis to the structure of the picture, which is determined by the physics of the image generation process. Candidates for contour points are the maximal magnitudes of the gray-value gradient for different scales in the direction of the gradient. Based on the output of such a bank of gradient filters, a procedure is proposed to select automatically a suitable scale, and with that, the size of the right convolution kernel. The application of poorly adapted filters, which make the exact localization of gray-value corners or T-, X-, and Y-junctions more difficult, is thus avoided. Possible gaps at such junctions are discussed for images of real scenes, and possibilities for the closure of some of these gaps are demonstrated when the extrema of the magnitudes of the gray-value gradients are used.</p>
picture processing; symbolic representation; gray-value variations; image function; image generation; contour points; gradient filters; convolution kernel; picture processing
A. Korn, "Toward a Symbolic Representation of Intensity Changes in Images," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 10, no. , pp. 610-625, 1988.