An adaptive speed function of level set method for moving object extraction

金沢大学理工研究域電子情報学系The convergence and stability of the level set method depend on the speed function. Therefore, it is important to define the speed function in a manner that is suitable for the individual application. In the present paper, we propose a novel speed function of the level set method for moving object extraction from a video sequence with a stationary background. The speed function focuses on the precision of moving object extraction. In the proposed extraction method, the outline between moving object regions and the background is estimated in advance based on the Gaussian noise distribution in the frame. The speed function is changed adaptively using the obtained outline in order to improve the convergence and precision of extraction. In addition, a new energy term in the direction of the contour of an object is incorporated into the speed function. The precision of the moving object extraction method using the proposed speed function is evaluated through computer simulations. ©2010 IEEE

Improvement of convergence and stability in moving object extraction by the level set method

金沢大学理工研究域電子情報学系Semantic object extraction from a video sequence is an indispensable technique in new content-based applications, such as in the international standards MPEG-4 and MPEG- 7. In the present paper, we propose a technique that extracts the shape of moving objects from a video sequence with a stationary background by the level set method. In the proposed method, two concepts are incorporated into a novel speed function of the level set method in order to improve convergence and stability. The first concept is the object map, which represents the outline of object regions and the background. The speed function is changed using the object map in order to improve convergence. The second concept is the contour potential energy, which represents the energy in the direction of an object\u27s contour. The efficiency of the proposed method for moving object extraction is demonstrated through computer simulations

Study on seam carving for image fingerprint

In past several years many image contents are distributed via internet. But illegal copy problem are rise up. Multimedia fingerprint techniques are tools for resist illegal copy. However today collusion attack such as average attack is appeared. Collusion attack is efficient method for breaking copyright protection scheme of image fingerprint. This paper presented an image fingerprint scheme to resistant collusion attack which is average attack especially. Proposed image fingerprint scheme is applied seam carving technique. Experimental results show that proposed image fingerprint scheme was good performance.2012 6th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2012;Palermo;4 July 2012through6 July 201

Watershed algorithm for moving object extraction considering energy minimization by snakes

金沢大学理工研究域電子情報学系MPEG-4, which is a video coding standard, supports object-based functionalities for high efficiency coding. MPEG-7, a multimedia content description interface, handles the object data in, for example, retrieval and/or editing systems. Therefore, extraction of semantic video objects is an indispensable tool that benefits these newly developed schemes. In the present paper, we propose a technique that extracts the shape of moving objects by combining snakes and watershed algorithm. The proposed method comprises two steps. In the first step, snakes extract contours of moving objects as a result of the minimization of an energy function. In the second step, the conditional watershed algorithm extracts contours from a topographical surface including a new function term. This function term is introduced to improve the estimated contours considering boundaries of moving objects obtained by snakes. The efficiency of the proposed approach in moving object extraction is demonstrated through computer simulations. © 2007 IEEE

A high-speed codebook design algorithm for ECVQ using angular constraint with search space partitioning

金沢大学大学院自然科学研究科情報システム金沢大学工学部In this paper, we propose a fast codebook generation algorithm for entropy-constrained vector quantization (ECVQ). The algorithm uses the angular constraint and employs a suitable hyperplane to partition the codebook and image data in order to reduce the search area and accelerate the search process in the codebook design. This algorithm allows significant acceleration in codebook design process. Experimental results are presented on image block data. These results show that our new algorithm performs better than the previously known methods

A fast matching pursuits algorithm using sub-band decomposition of video signals

金沢大学大学院自然科学研究科情報システム金沢大学工学部A high-efficiency video coding method using matching pursuits, which is a waveform coding technique, has recently been proposed. In this method, the motion compensated prediction error image is encoded by applying matching pursuits. In the present paper, we propose a matching pursuits coding method that encodes the sub-band images derived from motion compensated prediction error images. The complexity of the proposed method is reduced compared to the full-band matching pursuits because of lighter inner product computation due to reduction of both the resolution of the sub-band image and the basis function length of the dictionary. We evaluated the coding performance and computational complexity of the proposed method via computer simulations. © 2006 IEEE

非低エネルギー領域多段探索法によるMatching Pursuitsの高速化

金沢大学理工研究域電子情報学系A fast atom searching method for matching pursuits in a high-efficiency video coding system is described in this paper. The immense amount of operations is needed for the atom searching in matching pursuits, so speed-up in the searching algorithm is indispensable. We propose an atom searching algorithm that is based on both a correlation between the high signal-energy regions and optimal matching points and the correlation between the highly efficient approximated points, and to improve the computational complexity by reducing the searching points

Fast codeword search algorithm for ECVQ using hyperplane decision rule

金沢大学大学院自然科学研究科情報システム金沢大学工学部Vector quantization is the process of encoding vector data as an index to a dictionary or codebook of representative vectors. One of the most serious problems for vector quantization is the high computational complexity involved in searching for the closest codeword through the codebook. Entropy-constrained vector quantization (ECVQ) codebook design based on empirical data involves an expensive training phase in which Lagrangian cost measure has to be minimized over the set of codebook vectors. In this paper, we describe a new method allowing significant acceleration in codebook design process. This method has feature of using a suitable hyperplane to partition the codebook and image data. Experimental results are presented on image block data. These results show that our method performs better than previously known methods

Image content detection method using correlation coefficient between pixel value histograms

An extraction method for searching for unauthorized copies of an image on the Internet is required in image search to make use of digital watermarks. In this paper, we propose an efficient two-stage image search method for extraction of illegal copies of a target image. The first stage is a pre-search, which searches for candidate of illegal images by some simple method. The next stage is the main search, which extracts embedded copyright information from the candidate and decides whether the image is an illegal copy of the target. In addition, we propose a simple image search method which uses the correlation coefficient between pixel value histograms of images as a pre-search method. The proposed pre-search method is useful because the proposed method is possible to combine with the current extraction technologies of embedded information. The performance of the proposed pre-search method is evaluated through computer simulations. © 2011 Springer-Verlag

Improvement of convergence and stability in moving object extraction by the level set method

金沢大学理工研究域電子情報学系Semantic object extraction from a video sequence is an indispensable technique in new content-based applications, such as in the international standards MPEG-4 and MPEG- 7. In the present paper, we propose a technique that extracts the shape of moving objects from a video sequence with a stationary background by the level set method. In the proposed method, two concepts are incorporated into a novel speed function of the level set method in order to improve convergence and stability. The first concept is the object map, which represents the outline of object regions and the background. The speed function is changed using the object map in order to improve convergence. The second concept is the contour potential energy, which represents the energy in the direction of an object\u27s contour. The efficiency of the proposed method for moving object extraction is demonstrated through computer simulations