DocumentCode :
1743389
Title :
Shape recognition based on wavelet-transform modulus maxima
Author :
Cheikh, Faouzi Alaya ; Quddus, Azhar ; Gabbouj, Moncef
Author_Institution :
Signal Process. Lab., Tampere Univ. of Technol., Finland
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
461
Abstract :
In this paper we propose a new approach to object recognition based on the polygonal approximation of the object contour. The vertices of the polygon are the high curvature points of the contour, selected using the wavelet transform modulus maxima. We associate with this shape description a simple measure to estimate the similarity between objects. The description scheme and the similarity measure proposed take into consideration the way the human visual system perceives objects and compares them. The description scheme and the similarity measure can be used in several applications such as content-based indexing and retrieval, evaluation of segmentation results in the context of MPEG-4, or in classical classification problems. The proposed scheme is invariant to translation, rotation, scale change and noise corruption. Moreover, this description scheme allows accurate reconstruction of the shape boundary from the feature vector used to describe it. The experimental results and comparisons show the performance of the proposed technique
Keywords :
feature extraction; image classification; image reconstruction; image segmentation; wavelet transforms; MPEG-4; classification problems; content-based indexing; description scheme; feature vector; high curvature points; object contour; polygonal approximation; reconstruction; segmentation; shape recognition; similarity; wavelet-transform modulus maxima; Content based retrieval; Humans; Indexing; Laboratories; Object recognition; Retina; Shape measurement; Signal processing; Visual system; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Circuits and Systems, 2000. ICECS 2000. The 7th IEEE International Conference on
Conference_Location :
Jounieh
Print_ISBN :
0-7803-6542-9
Type :
conf
DOI :
10.1109/ICECS.2000.911579
Filename :
911579
Link To Document :
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