Title :
Line-Based Affine Invariant Object Location Using Transformation Space Decomposition
Author :
Yang, Richard ; Gao, Yongsheng
Author_Institution :
Sch. of Eng., Griffith Univ., Brisbane, Qld.
Abstract :
This paper presents a novel line-based affine invariant object location methodology. Our algorithm employs a new line-based transformation space decomposition technique to exploit intrinsic structural information provided by line features. Furthermore, we propose a new line-based distance transform to integrate with our algorithm to provide efficient transformation cell evaluation and subdivision in a coarse to fine manner. The algorithm is able to rapidly accelerate the searching process while maintaining high discriminative power and minimal storage requirement. The efficiency and discriminative power of this methodology are demonstrated using real-world examples with promising results
Keywords :
object recognition; transforms; line features; line-based affine invariant object location; line-based distance transform; line-based transformation space decomposition intrinsic structural information; transformation cell evaluation; transformation cell subdivision; Acceleration; Computer vision; Detectors; Image processing; Image segmentation; Machine vision; OFDM modulation; Object detection; Pattern recognition; Pixel;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.765