Integrating Low and High Level Object Recognition Steps

被引：0

作者：

Barta, Andras ^{[1
]}

Vajk, Istvan ^{[1
]}

机构：

[1] Budapest Univ Technol & Econ, Dept Automat & Appl Informat, H-1111 Budapest, Hungary

来源：

PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 11 | 2006年 / 11卷

关键词：

Object recognition; Bayesian network; Wavelets; Document processing;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.

引用

页码：126 / 131

页数：6

共 15 条

[1] [Anonymous], 1999, WAVELET TOUR SIGNAL
[2] BARTA A, 2005, T INFORM SCI APPL, V2, P1321
[3] Barta A, 2005, INFORM-J COMPUT INFO, V29, P291
[4] Burrus C.S., 1998, introduction to Wavelets and Wavelet Transforms-A Primer
[5] Document segmentation using polynomial spline wavelets
Deng, SL
Latifi, S
Regentova, E
[J]. PATTERN RECOGNITION, 2001, 34 (12) : 2533 - 2545
[6] Knowledge-directed vision: Control, learning, and integration
Draper, BA
Hanson, AR
Riseman, EM
[J]. PROCEEDINGS OF THE IEEE, 1996, 84 (11) : 1625 - 1637
[7] THE DESIGN AND USE OF STEERABLE FILTERS
FREEMAN, WT
ADELSON, EH
[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1991, 13 (09) : 891 - 906
[8] Neopolitan R., 2004, LEARNING BAYESIAN NE
[9] AN AUTOMATIC CIRCUIT DIAGRAM READER WITH LOOP-STRUCTURE-BASED SYMBOL RECOGNITION
OKAZAKI, A
KONDO, T
MORI, K
TSUNEKAWA, S
KAWAMOTO, E
[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1988, 10 (03) : 331 - 341
[10] Pearl J., 1989, Probabilistic reasoning in intelligent systems: networks of plausible inference, DOI DOI 10.1016/C2009-0-27609-4

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