Active contour energy used in object recognition method
Zhiheng Zhou, Kaiyi Liu, Xiaowen Ou · 2016
Object recognition finds wide application and is a challenge topic in computer vision and pattern recognition. In this paper, a new object detection method is proposed, which depends on active contour models (ACMs) energy function with pattern matching method. Firstly, object detection with shape prior based on energy function is presented to extract candidate targets. A novel geometric feature based on energy function of prior shape is put forward. The object detection method is invariant to scaling of shape and is also suitable for prior shapes set for general cases. Several candidate targets may be extracted when the object detection method is applied in object detection because most objects have similar shape. Then Speed up Robust Features (SURF) algorithm is employed to recognize the desired target from candidate targets. Experimental results show that proposed method is effective and efficient.