边缘与灰度检测相结合的场景图像文本定位

自然场景图像中包含大量的图像和文本信息，其文本字符能够提供重要的语义信息。利用计算机自动检测并识别自然场景中的文本信息，是模式识别和文字信息处理领域重要的研究内容。本文提出一种有效的从场景图像中定位文本的方法，其原理为：首先基于边缘检测进行文本区域粗定位，对定位到的区域进行灰度检测，来确定文本域中的字符位置，其后对所得到的检测区域进行筛选，去掉噪声区域，获取到目标文本域。实验结果表明，本文提出的方法对字体的大小、样式、颜色、以及排布方向具有较强的鲁棒性, 能够准确定位并提取自然场景下的文本信息。

Text extraction from scene image based on edge and gray-scale detection collaboration

Natural scene contains a large quantity of image information, and also a plenty of text information, while these text characters could offer important semantic information. Automatic detection and recognition of the text in natural scene image is an important research topic in pattern recognition and image processing field. In this paper, we propose an effective method to extract text from scene image. The main idea is as follows: First, an edge detection method is used for coarsely locating of the text areas, then we apply a gray based detection scheme to the located areas in order to confirm the founded characters. Finally, the noise regions are removed through filtering all the detected regions, and the target text regions are obtained. Experimental results show that our scheme is robust on finding the text in a natural scene image with respect to different font sizes, styles, colors and orientations, and could locate and extract the text information accurately.