DocumentCode
1637122
Title
A Pixel-level Statistical Structural Descriptor for Shape Measure and Recognition
Author
Zhang, Jing ; Wenyin, Liu
Author_Institution
Dept. of Comput. Sci., Univ. of South Florida, Tampa, FL, USA
fYear
2009
Firstpage
386
Lastpage
390
Abstract
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 spacestatistically. 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.
Keywords
computer vision; feature extraction; matrix algebra; shape recognition; statistical analysis; computer vision; feature space; histogram matrix; pixel-level statistical structural descriptor; shape measure; shape recognition; Computer science; Computer vision; Data mining; Dynamic programming; Feature extraction; Histograms; Length measurement; Shape measurement; Skeleton; Text analysis; measure; recognition; shape descriptor; statistical structural feature;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
Conference_Location
Barcelona
ISSN
1520-5363
Print_ISBN
978-1-4244-4500-4
Electronic_ISBN
1520-5363
Type
conf
DOI
10.1109/ICDAR.2009.175
Filename
5277660
Link To Document