激光与光电子学进展, 2019, 56 (12): 121001, 网络出版: 2019-06-13
基于Lab颜色空间纹理特征的图像前后景分离 下载: 1330次
Image Foreground-Background Separation Based on Texture Features Extracted in Lab Color Space
图像处理 图像前后景分离 区域生长 区域合并 图像子块 image processing image foreground-background separation region growing region merging image blocks
摘要
针对图像前后景分离的传统算法需要人机交互且分离效果差、效率低和种子点选取难等问题,提出了基于Lab颜色空间纹理特征的图像前后景自动分离算法。对图像进行分块,并将图像转换到由国际照明委员会(CIE)制定的CIE Lab颜色空间;然后提取各图像子块的颜色和纹理特征,选取种子点;最后采用区域生长算法得到分割图像,采用区域合并改善过分割现象。结果表明,所提算法的分离结果较好,处理时间和算法复杂度较传统算法更优。
Abstract
To address the problems of human-computer interaction, poor separation, low efficiency, and difficulty in seed selection in the traditional image foreground-background separation algorithms, we propose an automatic image-foreground-background separation algorithm based on the texture features extracted in the Lab color space. First, we segment the image into blocks and convert it into a CIE-Lab color space established by the international commission on illumination (CIE). Then, we extract the color and texture features of each image block and select seeds. Finally, we use a region growing algorithm for image separation and region merging to reduce over separation. The experimental results show that the proposed algorithm is superior to the traditional algorithm in terms of the separation results, processing time, and algorithmic complexity.
杨超, 刘本永. 基于Lab颜色空间纹理特征的图像前后景分离[J]. 激光与光电子学进展, 2019, 56(12): 121001. Chao Yang, Benyong Liu. Image Foreground-Background Separation Based on Texture Features Extracted in Lab Color Space[J]. Laser & Optoelectronics Progress, 2019, 56(12): 121001.