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An Image Retrieval Method Based on Color-Complexity and Spatial-Histogram Features

Wu H-C., Chang C-C.

Fundamenta Informaticae

2007

Vol. 76, nr 4

481-493

This paper proposes two kinds of image features. One feature is the spatial-histogram feature. It combines the color histogram feature and the information about the dimensional position of pixels in an image to record the distribution of the pixels' colors that are present in different spatial positions within an image. The other image feature proposed in this paper is the color-complexity feature, which can be used to describe the change of pixel colors in the image. From the experimental results, ANMRR value is provided and we observe that the image retrieval system based on these two kinds of image features can provide a fairly good accuracy rate in image retrieval. Moreover, it has the capacity to tolerate errors; that is, for images that are damaged by rotation, shift, or color variant attacks, their similar image pairs can still be retrieved from the image database. Thus, the accuracy and flexibility of the image retrieval system are drastically improved.

An Image Retrieval System Based on the Color, Areas, and Perimeters of Objects

Wang C-L., Hwang R-H., Chan Y-K, Chen C-Y., Cheng C-C.

Fundamenta Informaticae

2006

Vol. 69, nr 3

319-330

Two different objects can be generally distinguished by their colors, areas, and perimeters. This paper hence proposes an image retrieval system which uses the colors, areas, and perimeters of objects in an image as the features of the image. The system is insensitive to the shift and rotation variations of objects in images, as well as to the scale and noise variations of images. The experimental results show that this system is capable of recognizing different images very well.