this paper discusses image decomposition problem of the 3-layer MRC model based coding of scanned (noisy) document images. A widely-used approach for document decomposition is to divide the document image into blocks ...
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ISBN:
(纸本)9781424442195
this paper discusses image decomposition problem of the 3-layer MRC model based coding of scanned (noisy) document images. A widely-used approach for document decomposition is to divide the document image into blocks and split the pixel histogram of each block into two halves by minimizing the sum of variance of its pixels withthe mean of the halms. We propose to split a block by minimizing the variance of one half with its minimum pixel and the variance of the other half with its maximum pixel. Our goal is to increase the gap between the two halves by avoiding splitting of any cluster of pixels into both halves. It should help reduce complexity of the generated mask. Moreover, we do not decompose a block if it has no edge points, again to reduce the mask complexity. We also implement a noise reduction heuristic in the mask layer to correct placement of transition pixels. We provide simple analysis and evaluate block energy in terms of the DCT coefficients of the resulting FG/BG layer blocks. Experimental results show that code size of the mask layer of our test images, obtained using proposed processing is reduced to nearly half of the mask obtained by a straightforward 3-MRC implementation.
this paper proposes a transform domain data-hiding scheme for quality access control of images. the original image is decomposed into tiles by applying n-level lifting-based Discrete Wavelet Transformation (DWT). A bi...
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ISBN:
(纸本)9781424442195
this paper proposes a transform domain data-hiding scheme for quality access control of images. the original image is decomposed into tiles by applying n-level lifting-based Discrete Wavelet Transformation (DWT). A binary watermark image (external information) is spatially dispersed using the sequence of number generated by a secret key. the encoded watermark bits are then embedded into all DWT-coefficients of n(th)-level and only in the high-high (HH) coefficients of the subsequent levels using dither modulation (DM) but without complete self-noise suppression. It is well known that due to insertion of external information, there will be degradation in visual quality of the host image (cover). the degree of deterioration depends on the amount of external data insertion as well as step size used for DM. If this insertion process is reverted, better quality of images can be accessed. To achieve that goal, watermark bits are detected using minimum distance decoder and the remaining self-noise due to information embedding is suppressed to provide better quality of image. the simulation results have shown the validity of this claim.
Range images captured from range scanning devices such as laser scanners or PMD (photonic mixer device) cameras, often possess drawbacks of having low resolution and/or missing regions due to occlusions, reflectivity ...
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ISBN:
(纸本)9781424442195
Range images captured from range scanning devices such as laser scanners or PMD (photonic mixer device) cameras, often possess drawbacks of having low resolution and/or missing regions due to occlusions, reflectivity limited scanning area, sensor imperfections etc. In this work, we address boththe issues in a single framework. We employ Bayesian regularization for resolution enhancement and inpainting in a general multi-image super-resolution scenario. We modify the traditional image formation model used in image/range super-resolution to account for the missing regions. this modification is important to couple the inpainting process with super-resolution. We also stress the importance of prior information in the integration and note that we require the priors to constrain the solution differently for inpainting and for super-resolution. the proposed inhomogeneous prior handles the requirements for inpainting as well as super-resolution. the modification of the imaging model and the formulation of the inhomogeneous prior are both important for the success of the integration. Our results show inpainting of large missing regions, reduction in distortions and good preservation of details at the high-resolution.
An Experiential sampling and Meanshift tracker based Multi-view face detection in video is proposed in this paper In this framework, instead of performing face detection at every position in a frame, we determine cert...
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ISBN:
(纸本)9781424442195
An Experiential sampling and Meanshift tracker based Multi-view face detection in video is proposed in this paper In this framework, instead of performing face detection at every position in a frame, we determine certain key positions to run the multiview face detectors. these key positions are statistical samples drawn from a density function that is estimated based on color cues, past detection results, Meanshift tracker results and a temporal continuity model. these samples are then propogated using a Particle filter framework. We use a Meanshift tracker to track faces that are missed by the multiview face detectors. Our framework results in a significant reduction in computation time and accounts for the detection of complete 180 degree pose of the face. We also come up with a novel likelihood measure for track termination, which becomes important when used for detection purposes.
We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human act...
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ISBN:
(纸本)9781424442195
We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. the activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. the feature trajectories of an action category are learnt from training example videos using Dynamic Time Warping. the combined segmentation and the recognition processes are very efficient as boththe algorithms share the same framework and Gabor features computed for the former can be used for the later We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.
In several scientific areas, data are sampled irregularly and insufficiently due to practical and economical limitations. the use of such data in applications results in some artifacts and poor spatial resolution. the...
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ISBN:
(纸本)9781424442195
In several scientific areas, data are sampled irregularly and insufficiently due to practical and economical limitations. the use of such data in applications results in some artifacts and poor spatial resolution. therefore, before being used, the data are to be interpolated onto a regular grid. One of the methods achieving this objective is based on the Fourier reconstruction, which deals withthe under-determined system of equations. the Stagewise Orthogonal Matching Pursuit (StOMP) is a recently proposed greedy algorithm. Compared to the other recent algorithms like l(1) minimization techniques, StOMP admits certain promising features such as faster and simpler implementation even in large scale settings. the present work applies StOMP to the Fourier-based interpolation problem for the signals that have sparse Fourier spectra. the basic objective is to verify empirically the performance of the algorithm if and how far the measurement coordinates can be shifted from uniform distribution on the continuous interval. Taking kurtosis as a quantifier for the deviation of distribution from being uniform, we show numerically that the measurement coordinates can be significantly shifted from uniform distribution.
In this work, we propose a simple yet highly effective algorithm for tracking a target through significant scale and orientation change. We divide the target into a number of fragments and tracking of the whole target...
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ISBN:
(纸本)9781424442195
In this work, we propose a simple yet highly effective algorithm for tracking a target through significant scale and orientation change. We divide the target into a number of fragments and tracking of the whole target is achieved by coordinated tracking of the individual fragments. We use the mean shift algorithm to move the individual fragments to the nearest minima, though an), other method like integral histograms could also be used. In contrast to the other fragment based approaches, which fix the relative positions of fragments within the target, we permit the fragments to move freely within certain bounds. Furthermore, we use a constant velocity Kalman filter for two purposes. Firstly, Kalman filter achieves robust tracking because of usage of a motion model. Secondly, to maintain coherence amongst the fragments, we use a coupled state transition model for the Kalman filter Using the proposed tracking algorithm, we have experimented on several videos consisting of several hundred frames length each and obtained excellent results.
Bit Plane coding (BPC) constitutes an important component of the EBCOT Tier-1 block of JPEG2000 encoder. this paper proposes an efficient parallel hardware structure to implement the computation intensive word level b...
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ISBN:
(纸本)9781424442195
Bit Plane coding (BPC) constitutes an important component of the EBCOT Tier-1 block of JPEG2000 encoder. this paper proposes an efficient parallel hardware structure to implement the computation intensive word level bit plane coding algorithm. the proposed architecture computes the context and decision for all bit planes in parallel. the three coding passes are merged for all bit planes in a scan while the samples are coded in sequence. the proposed parallel BPC architecture offers a speed of 31 over the serial BPC architecture. Its memory requirement is independent of the size of the codeblock. the speed of the proposed architecture has been shown to be significantly faster than an architecture which has been recently reported in literature. the system architecture has been functionally verified by ModelSim and synthesized by TSMC 0.25 mu m vtvt CMOS cell libraries.
We propose an evolving scheme to detect slow as well as fast moving objects in a video sequence. the proposed scheme employ, both spatio-temporal and temporal segmentation to obtain the Video Object plane and hence de...
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ISBN:
(纸本)9781424442195
We propose an evolving scheme to detect slow as well as fast moving objects in a video sequence. the proposed scheme employ, both spatio-temporal and temporal segmentation to obtain the Video Object plane and hence detection. We propose a Compound Markov Random Field Model as the a priori image model that takes into account the spatial distribution of the current frame, temporal frames and the edge maps of the temporal frames. the spatio-temporal segmentation is cast as a pixel labeling problem and the labels are the MAP estimates. the MAP estimates of a frame are obtained by a hybrid algorithm. the spatial segmentation of a given frame evolves to generate the spatial segmentation of the subsequent frames. the evolved spatial segmentation together withthe temporal segmentation produces the Video Object Plane (VOP) and hence detection. Our scheme does require the computation of spatio-temporal segmentation of the initial frame thus speeding up the whole process. the results of the proposed scheme are compared with JSEG method are found to be better in terms of the misclassification error
this paper address new face verification scheme based on Log-Gabor filter (texture based) and Gaussian Mixture Model. the proposed method consists of three parts. the first part is a Log-Gabor filtering on facial imag...
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