TY - GEN
T1 - A pixel-level statistical structural descriptor for shape measure and recognition
AU - Zhang, Jing
AU - Wenyin, Liu
PY - 2009
Y1 - 2009
N2 - A novel shape descriptor based on the histogram matrix of pixel-level structural features is presented. First, length ratios and angles between the centroid and contour points of a shape are calculated as two structural attributes. Then, the attributes are combined to construct a new histogram matrix in the feature space statistically. The proposed shape descriptor can measure circularity, smoothness, and symmetry of shapes, and be used to recognize shapes. Experimental results demonstrate the effectiveness of our method. © 2009 IEEE.
AB - A novel shape descriptor based on the histogram matrix of pixel-level structural features is presented. First, length ratios and angles between the centroid and contour points of a shape are calculated as two structural attributes. Then, the attributes are combined to construct a new histogram matrix in the feature space statistically. The proposed shape descriptor can measure circularity, smoothness, and symmetry of shapes, and be used to recognize shapes. Experimental results demonstrate the effectiveness of our method. © 2009 IEEE.
UR - http://www.scopus.com/inward/record.url?scp=71449097309&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-71449097309&origin=recordpage
U2 - 10.1109/ICDAR.2009.175
DO - 10.1109/ICDAR.2009.175
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9780769537252
SP - 386
EP - 390
BT - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
T2 - ICDAR2009 - 10th International Conference on Document Analysis and Recognition
Y2 - 26 July 2009 through 29 July 2009
ER -