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Video summarization is an efficient and flexible way to represent video data. In this paper, we use the kernel PCA and clustering based key frame extraction to realize multilevel video representation. In order to remove the redundancy caused by large scene changes, SIFT flow scene alignment is performed on the clustering set of key frames. After alignment, one representative frame is chosen from the...
Threshold selection is the critical issue in image denoising. This paper deal with a new multiscale directional representation called the shearlet transform that has shown to represent specific classes of images with distributed discontinuities optimally. Techniques based on this transform for denoising using an efficient adaptive shrinkage threshold are presented. The shearlet transform not only...
Contourlet transform is a new multiscale and multidirectional image representation which effectively captures the edges and contours of images. Hidden Markov tree model (HMT) can capture all inter-scale, inter-direction and inter-location dependencies. Also, HMT can capture the statistical properties of the contourlet coefficients. Therefore, it is used to detect the image singularities (edges and...
A new algorithm for apple shape classification using level set and motion estimation was proposed. At first, a standard class shape apple images database was construct by expert, and then the level set representations according to signed distance transforms were used, which are a simple, robust, rich and efficient way to represent shapes; second, the unknown shape class apple was aligned to the standard...
In this paper, we present a new posture classification system to analyze different human activities directly from video sequence. For well recognizing each posture of an activity, we propose an adaptation of Radon transform called R-transform, which is invariant to common geometrical transformations, to represent low-level features. The advantage of the R transform lies in its low computational complexity...
Image searching and authentication have become strong requirements in the digital world. Image perceptual hashing has been proposed to meet them. In this paper, a rotation resilient image hashing algorithm is presented. In the algorithm, the position information of original image is extracted to adjust the rotation. Then the features of the image are extracted by contourlet transform. The key-dependence...
Detection of different kinds of shapes, i.e. lines, circles, hyperbolas etc., in varying kinds of images arises in diverse areas such as signal and image processing, computer vision or remote sensing. The generalized Hough transform is a traditional approach to detect a specific shape in an image by transforming the problem into a parameter space representation. In this paper we use the observation...
In this paper, we propose a new Non-symmetry and Anti-packing Model (NAM) representation method for gray image. By describing the NAM and Gray-Coded Bit-Plane Decomposition (GC-BPD), a novel NAM-based representation algorithm for gray image is presented. The theoretical analyses and experimental results show that the NAM-based representation method can reduce the data storage much more effectively...
Multi-scale decomposition (MSD) approaches are very useful in image processing and play an important role in image fusion algorithm. This paper proposes a novel image fusion algorithm using pyramidal empirical mode decomposition (PEMD). The principle of PEMD consists of performing a pyramid transform on intrinsic mode functions (IMF) and the residual image of empirical mode decomposition (EMD). The...
In this paper, we adopt constrained relaxation for distributed multi-view video coding (DMVC). The novel framework integrates the graph-based segmentation and matching to generate inter-view correlated side information without knowing the camera parameters. Moreover, graph-based representations of multi-view images are incorporated to form more distinctive feature constraints. The sparse data as a...
In this paper we address the problem of localisation and recognition of human activities in unsegmented image sequences. The main contribution of the proposed method is the use of an implicit representation of the spatiotemporal shape of the activity which relies on the spatiotemporal localization of characteristic, sparse, dasiavisual wordspsila and dasiavisual verbspsila. Evidence for the spatiotemporal...
One promising approach to remove motion deblurring is to recover one clear image using an image pair. Existing dual-image methods require an accurate image alignment between the image pair, which could be very challenging even with the help of user interactions. Based on the observation that typical motion-blur kernels will have an extremely sparse representation in the redundant curvelet system,...
Based on the analysis of the characteristics of electron probe image, This paper proposes a novel EPMA image fusion scheme based on contourlet transform. As a novel multiscale geometric analysis tool. Contourlet has shown many advantages over the conventional image representation methods. It provides flexible number of directions and captures the intrinsic geometrical structure of images. The efficient...
We present a novel classification scheme which uses partial object information that is selected adaptively using modified distance transform and represented as moment invariants (Hu moments) to compensate for scale, translation and rotational transformation(s). The moment invariants of different parts of an object are learned using AdaBoost algorithm [1]. The classifier obtained using the proposed...
This paper presents a comparative study between scale, rotation and translation invariant descriptors for shape representation and retrieval. Specifically, we studied Fourier, angular radial transform and image moment descriptors for shape representation. Since shape is one of the most widely used image feature exploited in content-based image retrieval systems, we studied for each descriptor, the...
Watermarking techniques are proposed as a solution to copyright protection of digital media files. Watermarking algorithms are mainly concentrated on spatial or spectral domains. In this work, a robust and high capacity watermarking method that is based on spatio-frequency (SF) representations is presented. We use the discrete evolutionary transform (DET) calculated by Gabor expansion to represent...
This paper presents a novel face recognition method based on the contourlet for facial features representation and using an new kernel based algorithm, for discriminating purposes, namely kernel relevance weighted discriminant analysis (KRWDA). This nonlinear reduction dimension algorithm has several interesting characteristics. First, using kernel theory, it handles nonlinearity efficiently. Second,...
We present an automatic system for off-line printed Amazigh handwritten characters recognition, based on an hybrid approach combining hidden Markov models (HMM) and the Hough transform. After preprocessing on the image of the character, the representative chain of the character is build from the Hough transformation. This chain is translated into sequence of observations that is used for the learning...
The problem of automatic object categorization is investigated under the proposed bag of feature object categorization framework. The framework consists of feature detection and representation which uses the scale invariant feature transform (SIFT) as local feature and bag of feature model to represent the image. Learning process utilizes k-NN (k-nearest neighbour). In this paper, we propose the dimensionality...
In this paper, we present a one dimensional descriptor for the two dimensional object silhouettes associated with each level of barycenter contour for multiple views shape matching and retrieval. Firstly, the barycenter contour is applied onto the shape contour. Then the averaging multi-triangle area representation (AMTAR) at each level of barycenter contour is computed as the shape descriptor. Finally,...
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