A SURVEY ON VARIOUS APPROACHES OF TEXT EXTRACTION IN IMAGES

T. Santhanam
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引用次数: 65

Abstract

Text Extraction plays a major role in finding vital and valuable information. Text extraction involves detection, localization, tracking, binarization, extraction, enhancement and recognition of the text from the given image. These text characters are difficult to be detected and recognized due to their deviation of size, font, style, orientation, alignment, contrast, complex colored, textured background. Due to rapid growth of available multimedia documents and growing requirement for information, identification, indexing and retrieval, many researches have been done on text extraction in images.Several techniques have been developed for extracting the text from an image. The proposed methods were based on morphological operators, wavelet transform, artificial neural network,skeletonization operation,edge detection algorithm, histogram technique etc. All these techniques have their benefits and restrictions. This article discusses various schemes proposed earlier for extracting the text from an image. This paper also provides the performance comparison of several existing methods proposed by researchers in extracting the text from an image.
图像文本提取的几种方法综述
文本提取在寻找重要和有价值的信息方面起着重要的作用。文本提取包括对给定图像中的文本进行检测、定位、跟踪、二值化、提取、增强和识别。这些文本字符由于其大小、字体、样式、方向、对齐、对比度、复杂的颜色、纹理背景的偏差而难以被检测和识别。由于现有多媒体文档的快速增长以及对信息、识别、索引和检索的需求日益增长,人们对图像中的文本提取进行了大量的研究。已经开发了几种从图像中提取文本的技术。该方法基于形态学算子、小波变换、人工神经网络、骨架化操作、边缘检测算法、直方图技术等。所有这些技术都有其优点和局限性。本文讨论了前面提出的从图像中提取文本的各种方案。本文还提供了研究人员提出的几种从图像中提取文本的方法的性能比较。
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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