http://jivp.eurasipjournals.com The latest research articles published by EURASIP Journal on Image and Video Processing 2013-05-21T00:00:00Z Compression of encrypted data draws much attention in recent years due to the security concerns in a service-oriented environment such as cloud computing. We propose a scalable lossy compression scheme for images having their pixel value encrypted with a standard stream cipher. The encrypted data are simply compressed by transmitting a uniformly subsampled portion of the encrypted data and some bitplanes of another uniformly subsampled portion of the encrypted data. At the receiver side, a decoder performs content-adaptive interpolation based on the decrypted partial information, where the received bit plane information serves as the side information that reflects the image edge information, making the image reconstruction more precise. When more bit planes are transmitted, higher quality of the decompressed image can be achieved. The experimental results show that our proposed scheme achieves much better performance than the existing lossy compression scheme for pixel-value encrypted images and also similar performance as the state-of-the-art lossy compression for pixel permutation-based encrypted images. In addition, our proposed scheme has the following advantages: at the decoder side, no computationally intensive iteration and no additional public orthogonal matrix are needed. It works well for both smooth and texture-rich images. http://jivp.eurasipjournals.com/content/2013/1/32 Xiangui Kang Anjie Peng Xianyu Xu Xiaochun Cao EURASIP Journal on Image and Video Processing 2013, null:32 2013-05-21T00:00:00Z doi:10.1186/1687-5281-2013-32 /content/figures/1687-5281-2013-32-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 32 2013-05-21T00:00:00Z PDF A new method to describe texture images using a hybrid combination of local and global texture descriptors is proposed in this paper. In this regard, a new adaptive local binary pattern (ALBP) descriptor is presented in order to carry out the local description. It is built by adding oriented standard deviation information to an ALBP descriptor in order to achieve a more complete representation of the images, and hence, it has been called adaptive local binary pattern with oriented standard deviation (ALBPS). Regarding semen vitality assessment, ALBPS outperformed previous literature works with an 81.88% accuracy and also yielded higher hit rates than the LBP and ALBP baseline methods. Concerning the global description of the images, several classical texture algorithms were tested and a descriptor based on wavelet transform and Haralick feature extraction (wavelet concurrent feature 13 (WCF13)) obtained the best results. Both local and global descriptors were combined, and the classification was carried out with a support vector machine. Two data sets have been evaluated: textures under varying illumination, pose and scale (KTH-TIPS) 2a data set and a second spermatozoa boar data set used to distinguish between dead or alive sperm heads. Therefore, our proposal is novel in three ways. First, a new local feature extraction method ALBPS is introduced. Second, a hybrid method combining the proposed local ALBPS and a global descriptor is presented, outperforming our first approach and all other methods evaluated for this problem. Third, texture classification accuracy is greatly improved with the two former texture descriptors presented. F score and accuracy values were computed in order to measure the performance. The best overall result was yielded by combining ALBPS with WCF13, reaching an F score = 0.886 and an accuracy of 85.63% in the spermatozoa data set and an 84.45% of hit rate in the KTH-TIPS 2a. http://jivp.eurasipjournals.com/content/2013/1/31 Oscar García-Olalla Enrique Alegre Laura Fernández-Robles María Teresa García-Ordás Diego García-Ordás EURASIP Journal on Image and Video Processing 2013, null:31 2013-05-10T00:00:00Z doi:10.1186/1687-5281-2013-31 /content/figures/1687-5281-2013-31-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 31 2013-05-10T00:00:00Z PDF The state-of-the-art video coding standard H.264/AVC achieves significant coding performance by adopting variable block sizes for motion estimation (ME) and mode decision. However, this technique brings out high computational complexity since the optimal mode is determined by exhaustively performing rate-distortion optimization (RDO) on each coding mode with different block sizes. In this paper, the fast intermode decision algorithm is proposed to reduce the computational complexity. Based on the high correlation between the residual error of ME and the optimal block size, general residual complexity (GRC) and local residual complexity (LRC) are defined. According to MB activity evaluated on GRC and LRC, candidate intermodes are determined and RDO processes are only performed on selected intermodes. The experimental results demonstrate that the proposed algorithm achieves time saving by 63% on average with negligible degradation of coding efficiency. http://jivp.eurasipjournals.com/content/2013/1/30 Jaeho Lee Seongwan Kim Kyungmin Lim Jae Hyun Kim Sangyoun Lee EURASIP Journal on Image and Video Processing 2013, null:30 2013-05-10T00:00:00Z doi:10.1186/1687-5281-2013-30 /content/figures/1687-5281-2013-30-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 30 2013-05-10T00:00:00Z PDF Fault diagnosis of induction motors in the practical industrial fields is always a challenging task due to the difficulty that lies in exact identification of fault signatures at various motor operating conditions in the presence of background noise produced by other mechanical subsystems. Several signal processing approaches have been adopted so far to mitigate the effect of this background noise in the acquired sensor signal so that fault-related features can be extracted effectively. Addressing this issue, this paper proposes a new approach for fault diagnosis of induction motors utilizing two-dimensional texture analysis based on local binary patterns (LBPs). Firstly, time domain vibration signals acquired from the operating motor are converted into two-dimensional gray-scale images. Then, discriminating texture features are extracted from these images employing LBP operator. These local feature descriptors are later utilized by multi-class support vector machine to identify faults of induction motors. The efficient texture analysis capability as well as the gray-scale invariance property of the LBP operators enables the proposed system to achieve impressive diagnostic performance even in the presence of high background noise. Comparative analysis reveals that LBP8,1 is the most suitable texture analysis operator for the proposed system due to its perfect classification performance along with the lowest degree of computational complexity. http://jivp.eurasipjournals.com/content/2013/1/29 Md Shahriar Tanveer Ahsan UiPil Chong EURASIP Journal on Image and Video Processing 2013, null:29 2013-05-08T00:00:00Z doi:10.1186/1687-5281-2013-29 /content/figures/1687-5281-2013-29-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 29 2013-05-08T00:00:00Z XML In this paper, we propose a variational segmentation model to deal with intensity inhomogeneity and Poisson noise. An energy functional is first proposed, which uses a data-fidelity term deduced from Poisson distribution instead of the usual L 2 norm as a measure of fidelity. Due to the new data-fidelity measure, this energy functional can fit the image intensity more accurately while it can diminish the influence of Poisson noise on segmentation results. We then reformulate the energy function as globally convex formulation, which allows for more flexible initialization. The final convex energy functional is minimized via the dual formulation instead of the usually used gradient descent method. Experimental results show that the proposed model can efficiently segment images with intensity inhomogeneity and Poisson noise. http://jivp.eurasipjournals.com/content/2013/1/28 Qiang Chen Chuanjiang He EURASIP Journal on Image and Video Processing 2013, null:28 2013-05-08T00:00:00Z doi:10.1186/1687-5281-2013-28 /content/figures/1687-5281-2013-28-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 28 2013-05-08T00:00:00Z XML In this research, a transition effect detection scheme for identifying possible highlight segments in baseball videos will be presented. The effects that are inserted manually by the broadcastersfor signaling the slow-motion segments will be extracted and the frames containing such effects can serve as anchor positions for further processing. A setof video segments will first be chosen to construct the `transition effect template' for the archived video. The candidate frames will be compared with this template for searching the slow-motion video segments. In baseball videos, we further construct the 'pitching view template' so that the starting positions of the video segments of interest can be located. By processing these segments only, we may further employ such method as hidden Markov model to classify their content. The major contribution of this research is the usage of compressed-domain features to achieve the efficiency. The experimental results show the feasibility of the proposed scheme. http://jivp.eurasipjournals.com/content/2013/1/27 Po-Chyi Su Chi-Heng Lan Chin-Song Wu Zi-Xin Zeng Wei-Yu Chen EURASIP Journal on Image and Video Processing 2013, null:27 2013-05-04T00:00:00Z doi:10.1186/1687-5281-2013-27 /content/figures/1687-5281-2013-27-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 27 2013-05-04T00:00:00Z PDF Nowadays, tags play an important role in the search and retrieval process in multimedia content sharing social networks. As the amount of multimedia contents explosively increases, it is a challenging problem to find a content that will be appealing to the users. Furthermore, the retrieval of multimedia contents, which can match users' current mood or affective state, can be of great interest. One approach to indexing multimedia contents is to determine the potential affective state, which they caninduce in users. In this paper, multimedia content analysis is performed to extract affective audio and visual cues from different music video clips. Furthermore, several fusion techniques are used to combine the information extracted from the audio and video contents of music video clips. We show that using the proposed methodology, a relatively high performance (up to 90%) of affect recognition is obtained. http://jivp.eurasipjournals.com/content/2013/1/26 Ashkan Yazdani Evangelos Skodras Nikolaos Fakotakis Touradj Ebrahimi EURASIP Journal on Image and Video Processing 2013, null:26 2013-04-30T00:00:00Z doi:10.1186/1687-5281-2013-26 /content/figures/1687-5281-2013-26-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 26 2013-04-30T00:00:00Z PDF Existing algorithms based on scale invariant feature transform (SIFT) edge-driven dual-bootstrap iterative closest point and Harris corners (Harris-partial intensity invariant feature descriptor (PIIFD)) have been shown to be robust in registering multimodal retinal images. However, they fail to register color retinal images with other modalities in the presence of large content or scale changes. Moreover, the approaches need preprocessing operations such as image resizing to do well. This restricts the application of image registration for further analysis such as change detection and image fusion. Motivated by the need for efficient registration of multimodal retinal image pairs, this paper introduces a novel integrated approach which exploits features of uniform robust scale invariant feature transform (UR-SIFT) and PIIFD. The approach is robust against low content contrast of color images and large content, appearance, and scale changes between color and other retinal image modalities like the fluorescein angiogram. Due to low efficiency of standard SIFT detector for multimodal images, the UR-SIFT algorithm extracts high stable and distinctive features in the full distribution of location and scale in images. Then, feature points are adequate and repeatable. Moreover, the PIIFD descriptor is symmetric to contrast, which makes it suitable for robust multimodal image registration. After the UR-SIFT feature extraction and the PIIFD descriptor generation in images, an initial cross-matching process is performed and followed by a mismatch elimination algorithm. Our dataset consists of 120 pairs of multimodal retinal images. Experiment results show the outperformance of the UR-SIFT-PIIFD over the Harris-PIIFD and similar algorithms in terms of efficiency and positional accuracy. http://jivp.eurasipjournals.com/content/2013/1/25 Zeinab Ghassabi Amin Sedaghat Jamshid Shanbehzadeh Emad Fatemizadeh EURASIP Journal on Image and Video Processing 2013, null:25 2013-04-28T00:00:00Z doi:10.1186/1687-5281-2013-25 /content/figures/1687-5281-2013-25-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 25 2013-04-28T00:00:00Z PDF In this paper, we propose a novel approach for estimating image similarity.This measure is of importance in assessing image correspondence or imagealignment and plays an important role in image registration. Currently, thisproblem is approached rather one-dimensionally since most registrationmethods consider the problem as either mono- or multi-modal. This perspectiveleads to the selection of some form of either the correlation coefficient(CC) or mutual information (MI) as image similarity measure (ISM). We proposea more generic framework for ISM construction, based on absolute jointmoments, which can be considered as a generalization of CC. Within thisframework, we propose a specific ISM that provides a different trade-off between MI andCC in terms of performance and computational cost for general registrationproblems. To illustrate this, we compared CC and MI with the proposed ISM andperformed extensive experiments with regard to accuracy, robustness andspeed. The evaluation demonstrated that the proposed absolute joint moments is a good combinationof properties of CC and MI, with respect to speed and performance. http://jivp.eurasipjournals.com/content/2013/1/24 Hrvoje Kalini¿ Sven Lon¿ari¿ Bart Bijnens EURASIP Journal on Image and Video Processing 2013, null:24 2013-04-26T00:00:00Z doi:10.1186/1687-5281-2013-24 /content/figures/1687-5281-2013-24-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 24 2013-04-26T00:00:00Z PDF This paper presents a fast context-based adaptive variable-length decoding (CAVLD) method of H.264/AVC with a very long instruction word-based bitstream processing unit (BsPU) designed for entropy decoding of multiple video formats. A new table mapping algorithm for the coeff_token, level, and run_before syntax elements of the quantized transform coefficients is proposed, and many branch operations are removed by utilizing several designated instructions in the BsPU. By applying designated instructions and the proposed table mapping algorithm to CAVLD, we found that the proposed fast CAVLD method achieves an increase of approximately 47% in the decoding speed and a reduction of approximately 59% in memory requirements for the table mapping. http://jivp.eurasipjournals.com/content/2013/1/23 Jung-Han Seo Hyun-Ho Jo Dong-Gyu Sim Doo-Hyun Kim Joon-Ho Song EURASIP Journal on Image and Video Processing 2013, null:23 2013-04-26T00:00:00Z doi:10.1186/1687-5281-2013-23 /content/figures/1687-5281-2013-23-toc.gif EURASIP Journal on Image and Video Processing 1687-5281 ${item.volume} 23 2013-04-26T00:00:00Z PDF