Title :
A new generalized affine moment invariants for shape retrieval and object recognition
Author :
Ding, Hao ; Li, Xudong ; Zhao, Huijie ; Xiao, Wen
Author_Institution :
Precision Opto-Mechatron. Technol. Key Lab. of Educ. Minist., Beihang Univ., Beijing, China
Abstract :
Shape retrieval and object recognition are two important tasks in pattern recognition society. Whether they can be achieved or not owes a lot to the performance of a descriptor primarily. In this paper, a new generalized affine moment invariants called illumination invariant MSA moments is proposed. This method combines the traditional AMI, MSA, MSA moment and the basic ideas used to construct illumination invariants. The results suggest that the new technique offers well discriminative power equivalent to the MSA in shape retrieval task, but is much more robust under illumination distortion and Gaussian noise. In 3D object recognition task, the proposed method outperforms both comparison methods under strong non-affine transformation.
Keywords :
Gaussian noise; affine transforms; distortion; image retrieval; lighting; object recognition; shape recognition; 3D object recognition task; AMI; Gaussian noise; descriptor performance; discriminative power equivalent; generalized affine moment invariants; illumination distortion; illumination invariant MSA moments; illumination invariants; nonaffine transformation; pattern recognition society; shape retrieval task; Lighting; Noise; Object recognition; Pattern recognition; Robustness; Shape; Transforms; MSA moment; illumination invariance; object recognition; pattern classification; shape retrieval;
Conference_Titel :
Instrumentation and Control Technology (ISICT), 2012 8th IEEE International Symposium on
Conference_Location :
London
Print_ISBN :
978-1-4673-2615-5
DOI :
10.1109/ISICT.2012.6291609