Abstract
An experiment on line extraction and pattern detection in a photograph is performed. From digitized pictures which have eight gray levels, the value and direction of the steepest descent is first calculated for each point with 3 × 3 meshes. Then those points whose gradient is more than certain threshold value are regarded as component points of line segments. From these points the estimation is done to extend the line portions as far as possible to the neighbouring ones. The pattern detection is done mainly for the photographs of human faces which are in front direction. A standard pattern of a front face is stored in a computer and the correlation values with several sizes of the standard pattern are calculated for the face contour, eyes, nose, and mouth independently. From these correlation values of the face portions, the final determination is done for the existence of a face. This two stage recognition process is adopted because certain portions of a face may be enough for the decision even if the other portion of a face is hidden in noise and could not be detected as such. For many photographs of human faces in several conditions the whole algorithm has been tested with considerable success.
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