DocumentCode :
2993790
Title :
Automated fast recognition and location of arbitrarily shaped objects by image morphology
Author :
Shih, Frank Y. ; Mitchell, O. Robert
Author_Institution :
Dept. of Comput. Inf. Sci., New Jersey Inst. of Technol., Newark, NJ, USA
fYear :
1988
fDate :
5-9 Jun 1988
Firstpage :
774
Lastpage :
779
Abstract :
Morphological operations are used for segmentation, feature generation and location extraction. A recursive adaptive thresholding algorithm transforms a gray-level image into a set of multiple level regions of objects. A distance transformation algorithm then is used to transform a binary image into the minimum distance from each object point to the object´s boundary. This algorithm uses a morphological erosion with a large structuring element which may correspond to Euclidean, city-block, or chessboard distance measures. A shape library database with hierarchical features is automatically generated. The features extracted are the shape number and the skeletal local-maximum points radii and coordinates. Object recognition is achieved by comparing the shape number and the hierarchical radii. Object location is detected by a hierarchical morphological bandpass filter
Keywords :
computerised pattern recognition; computerised picture processing; Euclidean distance; bandpass filter; binary image; chessboard distance; city-block; computerised pattern recognition; computerised picture processing; distance transformation algorithm; feature extraction; feature generation; gray-level image; image morphology; location extraction; recursive adaptive thresholding algorithm; segmentation; shape library database; shape number; skeletal local-maximum points radii; Band pass filters; Feature extraction; Image databases; Image segmentation; Libraries; Morphological operations; Object detection; Object recognition; Shape; Spatial databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1988. Proceedings CVPR '88., Computer Society Conference on
Conference_Location :
Ann Arbor, MI
ISSN :
1063-6919
Print_ISBN :
0-8186-0862-5
Type :
conf
DOI :
10.1109/CVPR.1988.196322
Filename :
196322
Link To Document :
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