The method consists in an automatic conversion of an input image to a set of binary ones in such a manner that each binary image stands for objects of approximate brightness. Contours are detected as boundaries of all objects of each binary image and are represented by the digital value 1 in a memory.
A circular operator (field) is used to follow the contours detected. To recognize a contour segment inside the operator field, the central element and at least two nonadjacent peripheral elements of the operator must have the digital value of 1. The contour segment is represented by a very simple graph consisting of one node labeled with the word “segment” and several arcs joined to the node and labeled with the attributes of the feature “segment” such as “direction, a;” “coordinates, X, Y;” “length, r;” “straight” or “curved;” and “contour;” where a, X, Y, and r are measures of the attributes. The operator is then translocated along the contour and for each of its positions the same graph is obtained: direction and position measures may differ, two consecutive nodes being joined by means of an arc denoted with the name “to adjoin.” Reduction of every two consecutive nodes to a single node is carried out when their direction measures are the same.
The recognized contour (i.e., converted to a graph) is compared with a set of reference (standard) graphs to be identified. Standard (reference) graphs may be achieved as a result of recognition processes of reference patterns.
KeywordsOperator Field Gray Level Input Image Binary Image Central Element
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