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Problem of loss compression taking into cosideration the structural components of signal distortion and compression technique unversality

100%

Berkman L. N. , Valchuk D.

tom Vol. 3, nr 1

42-59

In the paper, the outline of novel loss compression technique presents. The technique provides new possibilities: 1) a mechanism of loss compression quality rationalization into the space of quality indices, which are selected with a special purpose, 2) a mechanism of loss compression technique universality in sense of compressed signal heterogeneity and replacement of compression tasks of an end user. Besides those, a significant indication of the technique is its possibility of a signal structural distortion consideration. To realize this indication, we have selected pseudo-information measure JeK and studded its possibilities as a loss compression criterion for non-media signals. The measure exhibits several features that match experimental findings in multimedia perception.

Content-based image retrieval using a signature graph and a self-organizing map

86%

Van T. T. , Le T. M.

2016

tom Vol. 26, no. 2

423--438

In order to effectively retrieve a large database of images, a method of creating an image retrieval system CBIR (content-based image retrieval) is applied based on a binary index which aims to describe features of an image object of interest. This index is called the binary signature and builds input data for the problem of matching similar images. To extract the object of interest, we propose an image segmentation method on the basis of low-level visual features including the color and texture of the image. These features are extracted at each block of the image by the discrete wavelet frame transform and the appropriate color space. On the basis of a segmented image, we create a binary signature to describe the location, color and shape of the objects of interest. In order to match similar images, we provide a similarity measure between the images based on binary signatures. Then, we present a CBIR model which combines a signature graph and a self-organizing map to cluster and store similar images. To illustrate the proposed method, experiments on image databases are reported, including COREL, Wang and MSRDI.