首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >Integrating color into the local features based on the stable color invariant regions for image retrieval
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Integrating color into the local features based on the stable color invariant regions for image retrieval

机译:基于稳定的颜色不变区域将颜色集成到局部特征中以进行图像检索

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摘要

The local features of the objects are widely used in image matching and retrieval. The popular algorithms of the local feature detection are designed for gray images, which failed to make use of the color information in color images. However, the color information is absolutely nontrivial in the discrimination of different objects, vacancy of which would lead to miss-judgment. Although, some color invariants include a lot of color information, the local feature information has not been involved in the color invariants. The simple and efficient method to enhance the performance of the descriptors is to combine color with the local features. Generalized color moment and SIFT are chosen to make this combination in this paper. Because the calculation of the generalized color moment invariants is based on the regions in color image, the stable color invariant regions are first extracted through analyzing the reflection model of the object in the color image. Then, color and local features are fused to establish the framework of image retrieval based on color invariant regions. The robustness of our algorithm is strengthened and the time-consumption in matching is reduced compared to other algorithms.
机译:对象的局部特征被广泛用于图像匹配和检索。流行的局部特征检测算法是为灰度图像设计的,该算法无法利用彩色图像中的颜色信息。然而,颜色信息在区分不同物体时绝对是不平凡的,其空缺会导致判断失误。尽管某些颜色不变量包含许多颜色信息,但是局部特征信息尚未包含在颜色不变量中。增强描述符性能的简单有效方法是将颜色与局部特征结合起来。本文选择了广义色矩和SIFT来进行这种组合。由于广义色矩不变性的计算是基于彩色图像中的区域,因此首先通过分析彩色图像中对象的反射模型来提取稳定的色彩不变性区域。然后,融合颜色和局部特征,以建立基于颜色不变区域的图像检索框架。与其他算法相比,我们的算法具有更高的鲁棒性,并减少了匹配中的时间消耗。

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