基于小波的人类感知手写字符识别

Suzete E. N. Correia, J. Carvalho, R. Sabourin
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引用次数: 2

摘要

尽管在视网膜图像中发现了变化和扭曲,但人类视觉系统毫不费力地识别出熟悉的形状。本文提出了一种基于人类感知的手写体字符识别新方法。利用小波变换模拟视觉的多分辨率能力,提取水平、垂直和对角方向上的注视点和图像细节等特征。先前使用小波方向特征的系统使用NIST数字数据库获得了98.25%的识别率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human-perception handwritten character recognition using wavelets
The human vision system effortlessly recognizes familiar shapes despite changes and distortions found in retinal images. This work proposes a novel approach for recognition of handwritten characters based on human perception. The wavelet transform is used to simulate the multiresolutional capability of vision and to extract features such as fixation points and image details in horizontal, vertical and diagonal directions. A previous system which uses wavelet directional features yielded a recognition rate of 98.25% using the NIST numerals database.
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