DocumentCode :
1989654
Title :
Compressed differential angles as a feature in handwritten digit recognition
Author :
Kang, Seog Young
Author_Institution :
Dept. of Electr. & Comput. Eng., California State Polytech. Univ., Pomona, CA, USA
fYear :
1989
fDate :
6-8 Sep 1989
Firstpage :
75
Lastpage :
76
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;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multidimensional Signal Processing Workshop, 1989., Sixth
Conference_Location :
Pacific Grove, CA
Type :
conf
DOI :
10.1109/MDSP.1989.97034
Filename :
97034
Link To Document :
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