A NOVEL AFFINE INVARIANT FEATURE EXTRACTION FOR OPTICAL RECOGNITION

摘要：

In this paper, we propose a novel method for extracting the affine invariant features of images, named the new polar normalized histogram (NPNH).The feature of an image is extracted from a polar histogram bins originating from centroid of the mass to all other points in it with 5 bins for r and 24 bins for Θ.However, the traditional normalization is rotation variant since it normalizes the image only on two directions: vertical and horizontal.Thus the normalization of the image with different divergences on two directions is different from the normalization of its rotation.The most intuitive way to overcome the difficulty is normalizing the images on all directions.After new normalization, the number in each bin of polar histogram is counted and it is lined row by row to form a vector.Then, the Fourier spectrum of the vector, called Fourier descriptor, is computed.Finally, experimental results of Optical Character Recognition (OCR) are presented and show that the NPNH is a simple, affine invariant and powerful distance in object recognition.

关键词： Tracking Estimation Information fusion Resource management

作者: MELODY Z.W.LIAO LING WEI W.F.CHEN

作者单位: Faculty of Computer Science, Sichuan Normal University, Chengdu 610068, China Institute of Optics and Electronics, Chinese Academy of Science, Chengdu, China Key Lab of Medical Imaging, School of Biomedical Engineering, Southern Medical University, Guangzhou

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 1769-1773

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）