手写体数字识别中的压缩差角特征

S.Y. Kang
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引用次数: 0

摘要

只提供摘要形式。讨论了一种基于差分角度的特征提取方法。指针沿着骨架图像的连接路径移动。当它移动时,指针从参考点移动的角度被记录下来。由此得到一个微分角矢量,其元素由当前角度减去前一个角度得到。微分角矢量以这样一种方式处理,即去除(-45度,45度),(45度,-45度),(-90度,-90度),(90度,-90度)(135度,-135度),(-35度,135度)的孤立对;对最后的决定没有影响。微分角矢量中的一串零表示直线的存在。微分角矢量通过消除一串零中的所有零来压缩。当该点到达一个终点并且无法继续前进时,它将向后移动,直到到达图像的未遍历段。
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Compressed differential angles as a feature in handwritten digit recognition
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 degrees ,45 degrees ), (45 degrees ,-45 degrees ), (-90 degrees ,-90 degrees ), (90 degrees ,-90 degrees ) (135 degrees ,-135 degrees ), (-35 degrees ,135 degrees ) 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.<>
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