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With extensive usage of multimedia databases in real time applications, there arises a great need for developing efficient techniques to find the images from huge digital libraries. To find an image from a database, every image is represented with certain features. Texture and color are two important visual features of an image. In this paper we compare and analyze performance of image retrieval using...
This paper presents a new algorithm for content based image retrieval using color characteristics. The algorithm takes the Euclidean distance of color histogram between two images as the image similarity and consists of the following steps. First, it segments image into several blocks with the same size, and calculates the Euclidean distance of the color histogram between two arbitrary image blocks...
Color and shape descriptions of an image are the most widely used visual features in content-based image retrieval systems. Feature vectors for shape and color can be combined to improve the performance of the content-based image retrieval systems. In this paper, a novel image retrieval method integrating HSV color quantization and curve let transform is proposed. By analyzing properties of HSV(Hue,...
This paper describes a project that implements and tests a simple color histogram based search and retrieve algorithm for images. The study finds the technique to be effective as shown by analysis using the RankPower measurement. The testing also highlights the weaknesses and strengths of the model, concluding that the technique would have to be augmented and modified in order for practical use.
Most systems for content based image retrieval (CBIR) employ low level image features as a similarity measure. The problem of CBIR systems is that they are a ldquoblack boxrdquo to the user: Queries are specified by sample images, but the features which the CBIR system actually uses are unknown to the user. Hence, unexpected results are difficult to interpret. The problem becomes worse for inexperienced...
Content based image retrieval (CBIR) usually uses color features for representing images. The most common features of images are color histogram and color correlogram. The color correlogram was proposed to characterize not only the color distribution of pixels as in the case of color histogram, but also the spatial correlation of pairs of colors. Simple RGB values and their normal sequence r,g,b of...
This project presents an approach to index and retrieve images using a compact color descriptor in two color spaces namely HSV,and CIE L*u*v*. A compact color descriptor adopted in the proposed content-based image retrieval system is 127-bit binary Haar color histogram, which is used as an index of the images in the database. The color histogram is obtained for an image using a suitable color space...
Color feature of an image is the most common used feature in content-based image retrieval (CBIR) systems. Combining the traditional color-histogram with some spatial information will greatly increase the accuracy of matching two color images. One advantage of color feature is that it is independent to the distortion of an image. However, with the introducing of spatial information, this advantage...
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