The residue number system (RNS) has computational advantages in addition and multiplication compared with weighted number systems, such as the binary number system (BNS), since operations on residue digits are perform...
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The residue number system (RNS) has computational advantages in addition and multiplication compared with weighted number systems, such as the binary number system (BNS), since operations on residue digits are performed independently and these processes can be performed in parallel. Thus they are widely used in digital signal processing etc. Since residue to binary conversion is critical and difficult for the practicality of RNS, in this paper, a novel residue to binary (R/B) conversion algorithm for the restricted moduli set (2/sup n/ -1, 2/sup n/, 2n+1), based on exploring the periodicity of modulo (2/sup n/ /spl plusmn/ 1) operations is presented. A new 2n-bit adder based R/B converter is also proposed. The performance comparison results demonstrate that the new converter is faster and requires less area compared with the others reported in the previous literature.
A new parallel-based lifting algorithm (PBLA) for the 9/7 filters, exploring the parallelism of arithmetic operations in each lifting step, was proposed in this paper. It shortened significantly the critical path of c...
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ISBN:
(纸本)0780384032
A new parallel-based lifting algorithm (PBLA) for the 9/7 filters, exploring the parallelism of arithmetic operations in each lifting step, was proposed in this paper. It shortened significantly the critical path of computation, and resulted in a fast VLSI implementation architecture. In comparison with the conventional lifting algorithm based implementation (CLABI), the latency is reduced by more than half from (4T/sub m/ + 8T/sub a/) to (T/sub m/ + 4T/sub a/), which is competitive to that of convolution based implementation CBI, and can be further reduced to Tm by inserting 3 stages of pipeline. The experimental results demonstrate that the proposed architecture has good performances in both speed and area.
Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occup...
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Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occupant and the position of the occupant's head. This work presents a method for classification and occupant's head detection based on passive stereo vision. The proposed system uses depth surface analysis and scene statistics together with support vector machines for classification and selection of head candidates. Evaluation of the method shows 99% correct for classification and 98% correct for head detection, using large sets of image data, and image sequences recorded in a driving vehicle.
A new approach for the personal identification using hand images is presented. This paper attempts to improve the performance of palmprint-based verification system by integrating hand geometry features. Unlike other ...
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Given the fundamental matrix between a pair of images taken by a nonstationary projective camera with constant internal parameters, we show how to use the two independent Kruppa equations in order to explicitly cut do...
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An algorithm for contour matching is presented in this paper. It is implemented in two steps: firstly, bottom-up, corners are matched, the matched corner points guide line segment matching, and then the matched line s...
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A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss func...
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Head detection is an important, but difficult task, if no restrictions such as static illumination, frontal face appearance or uniform background can be assumed. We present a system that is able to perform head detect...
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A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss func...
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A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss func...
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ISBN:
(纸本)076951695X
A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties. The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples. The performance in the experiments is better than those of two popular methods.
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