Text localization using DWT fusion algorithm

Tianding Chen
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引用次数: 4

Abstract

Texts provide highly condensed information about the contents of images or video sequences. It proposes a text localization method using discrete wavelet transform and neural network. Because of the property of Harr wavelet transform, the proposed approach can localize large font size text by merging 4 small block wavelet coefficients into large one. Then the morphological dilation operation and the neural network are employed to raise the recall rate and precision rate. Experimental results show that the proposed method can successfully locate text region from complex images. Its precision rate is better than that of other methods.
基于DWT融合算法的文本定位
文本提供了关于图像或视频序列内容的高度浓缩的信息。提出了一种基于离散小波变换和神经网络的文本定位方法。该方法利用Harr小波变换的特性,将4个小块小波系数合并为一个大块小波系数,实现了对大字体文本的局部定位。然后采用形态扩张运算和神经网络相结合的方法提高查全率和查准率。实验结果表明,该方法可以成功地从复杂图像中定位文本区域。其精度优于其他方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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