为了提取区域边界，可以对图像直接运用一阶微商算子或二阶微商算子，然后根据各像点处的微商幅值或其他附加条件判定其是否为边界点。如果图像中含有较强噪声，直接进行微商运算将会出现许多虚假边界点。-.Using the feature of distinct edge contour existing between the text and the background regions in color images, a novel text extraction algorithm—CEMA(Co

一篇关于文字识别中文本抽取的英文论文，适用于复杂背景的图像。-Article on the Chinese character recognition in English of the selected papers for complex background image.

The basic steps of the connected-component text extraction algorithm are given below, and diagrammed in Figure 10. The details are discussed in the following sections. 1. Convert the input image to YUV color space. The luminance(Y) value is used

The basic steps of the edge-based text extraction algorithm are given below 1. Create a Gaussian pyramid by convolving the input image with a Gaussian kernel and successively down-sample each direction by half. (Levels: 4) 2. Create directiona

object classification using recognized scene text in natural images. While the state-of-the-art relies on visual cues only, this paper is the first work which proposes to combine textual and visual cues. Another novelty is the textual cue extraction.