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Texts appearing on compound image are usually classified into scene text and imposed text. Imposed text, like scripts in videos, slogans in advertisements and titles in magazine covers, contains important information. In this paper, a multistep compression method that could preserve imposed text quality in restored image is presented. The method separates imposed text from background and compresses...
A novel skin detection method in JPEG compressed domain has been proposed in this paper. Color and texture features of the image blocks are extracted from the entropy decoded DCT coefficients firstly. Then, data mining method, i.e. decision tree, is applied to establish the skin color model to describe the relationship between the features of image blocks and the skin detection results, afterwards,...
Video processing for surveillance and security applications has become a research hotspot in the last decade. This paper reports a research into volume-based segmentation techniques for video event detection. It starts with an introduction of the structure in 3D video volumes denoted by spatio-temporal features extracted from video footages. The focus of the work is on devising an effective and efficient...
Image quality is often degraded by blur caused by, for example, misfocused optics or camera motion. Blurring may also deteriorate the performance of computer vision algorithms if the image features computed are sensitive to these degradations. In this paper, we present an image descriptor based on local phase quantization that is robust to centrally symmetric blur. The descriptor referred to as local...
This paper describes a compression technique for printed document images and string matching method on the compressed images.To send digitized document images over the Web, compression of the document images is required. Moreover, in order to deal with historical letterpress printing collections, it is important to provide a full-text search method for them.The proposed compression scheme is based...
To exploit the road network in raster maps, the first step is to extract the pixels that constitute the roads and then vectorize the road pixels. Identifying colors that represent roads in raster maps for extracting road pixels is difficult since raster maps often contain numerous colors due to the noise introduced during the processes of image compression and scanning. In this paper, we present an...
In this paper, a novel approach is proposed to estimate camera motion and segment moving objects from compressed video streams, aiming to detect semantic events in video clips. Simultaneously using the motion vectors and DC components of MPEG macroblocks (MB), the camera motion type and motion parameters of each frame are estimated with simplified models. Then the segmentation of moving objects is...
This work presents a fast algorithm, namely 2-D symmetric mask-based discrete wavelet transform (SMDWT), to address some critical issues of the 2-D discrete wavelet transform (DWT). Unlike the traditional DWT involving dependent decompositions, the SMDWT itself is subband processing independent, which can significantly reduce complexity. Moreover, DWT cannot directly obtain target subbands, which...
Segmentation of semantic video object planes (VOPpsilas) from video sequence is a key to the standard MPEG-4 with content-based video coding. In our paper, we propose an automatic segmentation algorithm under static background. The algorithm can extract accurate video objects from slow moving video sequences. The initial two coarse masks are first obtained based on frame difference and motion detection,...
The goal of blind steganalysis is to detect the presence of hidden data and to eventually extract them from the stego images generated by various data hiding schemes. In this paper, we construct a new blind classifier capable of detecting several steganographies for JPEG images. Thirteen statistics are collected in the DCT domain and spatial domain. By using the characteristic function and the center...
Easy availability of internet, together with relatively inexpensive digital recording and storage peripherals has created an era where duplication, unauthorized use and maldistribution of digital content has become easier. To prevent unauthorized use, misappropriation, misrepresentation; authentication of multimedia contents achieved a broad attention in recent days. In this regard we've already introduced...
In this paper an incremental classification scheme for large data sets and images is proposed in the form of a two-stage computation scheme. First, information compression of the original data set or pixels is performed by a modification of the neural-gas unsupervised learning algorithms. Then two features are extracted from the obtained compressed information model, namely the center-of-gravity of...
We consider here image segmentation as a problem of clustering texture features by frequency content. Specifically, we develop a low complexity algorithm for image segmentation that operates directly on the bitstream of JPEG compressed images. Using morphological filtering and watersheds, the algorithm effectively segments an image by combining areas of similar frequency content. Its low complexity...
When we generate an intermediate viewpoint image using multi-view images and their depth maps, we may have very annoying boundary noises in the background due to depth value errors around depth discontinuities. In this paper, we propose a boundary filtering method for synthesized images. After defining the boundary noise area using depth map, we replace them with corresponding texture information...
Sketch based image coding decomposes an input image into a piece-wise smooth approximation image and a residual image. Image compression by gradient field integration follows this model, but differs by generating the approximation image from gradient data along edge contours and regularly sampled low resolution image data. This allows direct and efficient calculation of an approximation image which...
This paper proposes a computational scheme for comparison and color analysis of images by using unsupervised learning algorithms. As a first step, two special growing unsupervised learning algorithms are introduced and used to create the so called compressed information model (CIM) which replaces the original ldquoraw datardquo (the RGB pixels) of the image with a much smaller number of neurons. Then...
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