摘要
颜色特征能够有效地表征图像的颜色分布。但是,现有的颜色特征提取算法基于单一色彩空间,颜色矩作为最常用的全局颜色特征向量,往往会因为忽略图像的空间特征导致检索错误。针对上述不足,提出了一种基于混合色彩空间分块颜色特征提取算法,并将所提取的颜色特征与纹理特征相结合,用于图像的分类识别中。实验结果证明:无论是国画还是普通图像,分类识别过程中,本文算法相比普通的单一色彩空间颜色特征提取算法,其查准率和查全率均得到明显提高,并且图像分块之后,其查准率和查全率还能进一步提高。
The color feature can effectively characterize the color distribution of images. However, most of the existing algorithms are based on a single color space, and the color moment is the most commonly used as global color feature vector, thus the lack of color spatial information lead to retrieval errors. Aiming at the problems, a block color feature extraction algorithm based on the mixed color space is proposed. The extracted color feature and texture feature are combined for classification and recognition of image. Experimental. results show that the precision and recall of the color feature extraction algorithm in the mixed color space are improved in the process of classification and identification for Chinese painting and general image, when it compared with the single color space feature extraction algorithm. And they are further enhanced after image segmentation.
出处
《激光与光电子学进展》
CSCD
北大核心
2018年第1期252-258,共7页
Laser & Optoelectronics Progress
基金
国家自然科学基金(61373112)
住房和城乡建设部科学技术项目计划(2016-R2-045)
陕西省自然科学基础研究资金(2014JM8343)
关键词
图像处理
图像特征提取
颜色矩
混合色彩空间
分块特征提取
image processing
image feature extraction
color moment
mixed color space
block feature extraction
