Abstract:A sample vector formation method is presented to decrease the effect of the rotated characters on recognition rate. Firstly, the invariant features are extracted, such as centroid and principal axis. Then, the coordinate transformation is carried out and the image is converted to the polar coordinate system. Finally, the pixels are re-arranged according to the rules. The recognition is carried out directly on the gray-level images by adopting the improved PCA subspace method. Experimental results show that the proposed method can decrease the number of sieving samples with a higher recognition rate, compared with the typical method.
宋怀波,路长厚,李建美,卢国梁. 标牌图像的旋转不变性矢量提取及其PCA子空间识别*[J]. 模式识别与人工智能, 2008, 21(6): 824-830.
SONG Huai-Bo, LU Chang-Hou, LI Jian-Mei, LU Guo-Liang. Rotate Invariant Vector Extraction of Pressed Protuberant Characters on Metal Label and PCA Based Recognition. , 2008, 21(6): 824-830.
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