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机构地区:[1]辽宁师范大学计算机与信息技术学院,大连116029
出 处:《模式识别与人工智能》2012年第2期313-317,共5页Pattern Recognition and Artificial Intelligence
基 金:国家自然科学基金资助项目(No.60773031;60873222)
摘 要:以对立色度空间及Zernike矩理论为基础,提出一种基于Zernike色度分布矩的彩色图像检索方法.该方法首先将彩色图像从三维RGB颜色空间转换到二维对立色度空间,以获得图像像素的色差度量值.然后结合Zernike矩相关知识,在二维色度空间中计算出各像素的Zernike色度分布矩,最后将Zernike色度分布矩作为图像颜色特征,并进行彩色图像检索.仿真实验表明,该算法能够准确高效地查找出用户所需内容的彩色图像,并且具有较好的查准率和查全率.Feature extraction and representation are important to the content-based image retrieval (CBIR). Color is one of the widely used visual features and it is invariant to image size and orientation. According to the opponent chromaticity space and Zernike moments, a color image retrieval using Zernike chromaticity distribution moments is proposed. Firstly, the image is transformed from RGB space to opponent chromaticity space. Then, the characteristics of the color contents of an image are captured by using Zernike chromaticity distribution moments directly from the chromaticity space. Finally, the similarity between color images is computed by Zernike chromaticity distribution moments. The experimental results show the effectiveness of the proposed algorithm in improving the retrieval performance.
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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