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EN
The problem investigated in this paper refers to image retrieval based on its compressed form, hence giving much advantages in comparison to traditional methods involving image decompression. The main goal of this paper is to discuss a unified visual descriptor for images stored in the two most popular image formats – JPEG/JFIF and JPEG-2000 in the aspect of content-based image retrieval (CBIR). Since the problem of CBIR takes a special interest nowadays, it is clear that new approaches should be discussed. To achieve such goal a unified descriptor is proposed based on low-level visual features. The algorithm operates in both DCT and DWT compressed domains to build a uniform, format-independent index. It is represented by a three-dimensional color histogram computed in CIE L*a*b* color space. Sample software implementation employs a compact descriptor calculated for each image and stored in a database-like structure. For a particular query image, a comparison in the feature-space is performed, giving information about images' similarity. Finally, images with the highest scores are retrieved and presented to the user. The paper provides an analysis of this approach as well as the initial results of application in the field of CBIR.
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