Title :
Covariant support region and detection algorithm based on LoG corners
Author :
Liu, Yawei ; Li, Jianwei
Author_Institution :
Key Lab. on Opto-Electron. Tech. of State Educ. Minist., Chongqing Jiaotong Univ., Chongqing, China
Abstract :
Detection of local feature covariant region is a new technology of image contents and image semantic representations, and it has become an important foundation of the image recognition, learning and understanding. First, a Laplace of Gaussian corner detection method is proposed based on edge contour curves, in the meantime, a new local feature descriptor, named covariant support region, is introduced. Then, a detection algorithm of covariant support region is framed, which is covariant for rotation and scale transformation. Comparing with previous studies, the computational complexity of proposed algorithm is significantly reduced by this method. The experiments data indicate that the method proposed in this paper has good performance on higher accuracy, higher repeatability, and lower complexity.
Keywords :
computational complexity; edge detection; image representation; Gaussian corner detection method; LoG corners; computational complexity; covariant support region detection algorithm; edge contour curves; image content representation; image recognition; image semantic representations; local feature covariant region detection; local feature descriptor; Biomimetics; Computational complexity; Detection algorithms; Detectors; Image edge detection; Image recognition; Image reconstruction; Object detection; Robot vision systems; Surface reconstruction;
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-4774-9
Electronic_ISBN :
978-1-4244-4775-6
DOI :
10.1109/ROBIO.2009.5420847