基于72树和遗传算法的图像检索

Liang Lei, Jun Peng, Bo Yang
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引用次数: 1

摘要

在基于内容的图像检索系统中,颜色、纹理和形状信息一直是原始图像描述符。然而,如何快速检索图像是一个挑战,因为从网络图像中检索图像的速度和效率是最重要的。采用遗传算法对基于HSV色彩空间的方法进行改进,优化了计算量。首先,介绍了基于HSV色彩空间的图像主色提取方法。然后介绍了如何利用遗传算法对主色提取算法进行优化。最后,利用遗传算法对图像进行相似性度量。基于Corel数据库的实验和结果表明,该方法在时间和精度上都有很大的提高。
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Image retrieval based on 72-trees and genetic algorithm
Color, texture and shape information have been the primitive image descriptors in content based image retrieval systems. However, how to quickly retrieving images is a challenge because that the speed and efficiency of retrieving image from Internet image is most important. We used genetic algorithm to improve the method based on HSV color space, and optimized the computational workload. First, the paper introduces how to extract dominant color of an image based on HSV color space. Then, it describes how to use genetic algorithm to optimize the algorithm of extracting dominant color. In the end, genetic algorithm is be used for the similarity measure of images. The experiments and results, which based on Corel database, showed that this method has greatly improved the image retrieval in time and precision rates.
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