Author_Institution :
Dept. of Electr. & Comput. Eng., California State Polytech. Univ., Pomona, CA, USA
Abstract :
Summary form only given. A feature extraction method using differential angles is discussed. A pointer follows a connected path along a skeletonized image. As it moves along, angles of the pointer movement from reference are recorded. From this, a differential angle vector, whose element is obtained by subtracting the previous angle from the current angle, is obtained. The differential angle vector is processed in such a way that isolated pairs of (-45°,45°), (45°,-45°), (-90°,-90°), (90°,-90°) (135°,-135°), (-35°,135°) are removed; there is no effect on the final decision. A string of zeros in the differential angle vector indicates the existence of a straight line. The differential angle vector is compressed by eliminating all zeros in a string of zeros. When the point reaches an end point and no further advancement is possible, it moves backward until reaching an untraversed segment of image
Keywords :
picture processing; backward error propagation network; compressed differential angles; differential angle vector; feature extraction method; handwritten digit recognition; Feature extraction; Handwriting recognition; Image coding; Image segmentation; Machine intelligence; Neural networks; Shape; Skeleton;