This paper presents an enhanced multi-level filter algorithm and its Very Large Scale Integration (VLSI) architecture for infrared imageprocessing. The modified multi-level filter algorithm resolves the splitting tar...
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This paper presents an enhanced multi-level filter algorithm and its Very Large Scale Integration (VLSI) architecture for infrared imageprocessing. The modified multi-level filter algorithm resolves the splitting targets problem using Gaussian pyramid processing. Owning three filtering paths, the proposed VLSI architecture of the filter can simultaneously enhance small targets with different sizes in infrared images. Some design techniques in implementing hardwired multiplication, subsample and asynchronous FIFO have been presented. This VLSI architecture has been implemented using Semiconductor Manufacturing International Corporation (SMIC) 0.35 mu m 4-layer CMOS technology. The simulation results show that it not only effectively suppresses background, eliminates noise and enhances small targets in an infrared image comparing with other small target detective methods, but also meets infrared image real-time processing requirements (5M similar to 10M pixels/s). The implemented filter chip consists of 60,284 gates and 8 K Static Random Access Memory (SRAM), operates at 50 MHz.
A novel improved broyden's method has been presented to estimate image jacobian matrix for uncalibrated visual servoing. In this paper, we apply chebyshev polynomial as a cost function to approximate best value. C...
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ISBN:
(纸本)9780819469526
A novel improved broyden's method has been presented to estimate image jacobian matrix for uncalibrated visual servoing. In this paper, we apply chebyshev polynomial as a cost function to approximate best value. Compared with recursive least square (RLS) algorithm which is restricted by the prior knowledge for obtaining some performances, chebyshev polynomial algorithm has a great adaptability to estimate jacobian parameter, even without the prior knowledge. A microscopic image jacobian model has been developed for the four degree-of-freedom micromanipulator in our microassembly system. The performance has been confirmed by simulations and experiments.
A contour detection model, inspired by the behavior of the primary visual cortex, is presented. The response of a central stimulus in the receptive field is affected by the presence of surrounding stimuli - for some s...
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A contour detection model, inspired by the behavior of the primary visual cortex, is presented. The response of a central stimulus in the receptive field is affected by the presence of surrounding stimuli - for some stimulus conditions, the response is suppressed and for other conditions the response is enhanced. The visual mechanisms of contextual influences are utilized to extract "coherent" configurations. This is mainly due to the following two reasons: (1) on the one hand, a smooth contour can yield collinear excitation, which highlights smooth contours from irregularly textured surround;(2) on the other hand, similar orientation textures receive iso-orientation surround suppression and region boundary is subjected to the less inhibition, which makes boundary more salient for perceptual pop-out. Accordingly, smooth contours progressively stand out from their surround and at the same time textures are gradually suppressed by their surround through dynamic fine-tuning of contextual information. The proposed method which distinguishes between contours and texture edges is more effective for contour-based object recognition tasks. Initial experiments show that the model can be successfully applied to contour detection. Especially, when object contours are lumped together with unwantedly cluttered surround, the advantage of our approach is more prominent. This study provides a biological scheme for contour detection in computer vision. (c) 2006 Elsevier B.V. All rights reserved.
In traditional Direct Torque control (DTC), speed regulator is widely based on conventional Proportional Integral Derivative (PID) controller, which has to depend on precise math model of the subject. However, PID can...
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ISBN:
(纸本)9781424407361
In traditional Direct Torque control (DTC), speed regulator is widely based on conventional Proportional Integral Derivative (PID) controller, which has to depend on precise math model of the subject. However, PID cannot easily achieve swift response, small overshooting and fine speed control precision especially in low speed range. This paper introduces a nonlinear control tcchnology-Auto Disturbance Rejection controller (ADRC) into DTC to improve the speed adaptation capability and robustness, and a parameter design method of stator flux estimation is proposed. The simulation results prove the system has good control performance.
In this paper, a face recognition method using local qualitative representations is proposed to solve the problem of face recognition in varying lighting. Based on the observation that the ordinal relationship between...
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ISBN:
(纸本)9780819469526
In this paper, a face recognition method using local qualitative representations is proposed to solve the problem of face recognition in varying lighting. Based on the observation that the ordinal relationship between the average brightness of image regions pair is invariant under lighting changes, Local Binary Mapping is defined as an illumination invariant for face recognition based on Local Binary Pattern descriptor, which extracts the local variance features of an image. For the 'symbol' feature vector, hamming distance is used as similarity measurement. It has been proved that the proposed method can provide the accuracy of 100 percent for subset 2, 3, 4 and 98.89 percent for subset 5 of the Yale facial database B when all images in subset 1 are used as gallery.
Vessel segmentation is the base of three dimensional reconstruction on digital subtraction angiography (DSA) images. In this paper we propose two simple but efficient methods of vessel segmentation for DSA images. The...
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Vessel segmentation is the base of three dimensional reconstruction on digital subtraction angiography (DSA) images. In this paper we propose two simple but efficient methods of vessel segmentation for DSA images. The original DSA image is divided into several appropriate subimages according to a prior knowledge of the diameter of vessels. We introduce the vessels existence measure to determine whether each subimage contains vessels and then choose an optimal threshold, respectively, for every subimage previously determined to contain vessels. Finally, an overall binarization of the original image is achieved by combining the thresholded subimages. Experiments are implemented on cerebral and hepatic DSA images. The results demonstrate that our proposed methods yield better binary results than global thresholding methods and some other local thresholding methods do. (c) 2006 Elsevier B.V. All rights reserved.
The scale-invariant feature detecting methods always require a lot of computation yet sometimes still fail to meet the real-time demands in robot vision fields. To solve the problem, a quick method for detecting inter...
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ISBN:
(纸本)9780819469540
The scale-invariant feature detecting methods always require a lot of computation yet sometimes still fail to meet the real-time demands in robot vision fields. To solve the problem, a quick method for detecting interest points is presented. To decrease the computation time, the detector selects as interest points those whose scale normalized Laplacian values are the local extrema in the nonholonomic pyramid scale space. The descriptor is built with several subregions, whose width is proportional to the scale factor, and the coordinates of the descriptor are rotated in relation to the interest point orientation just like the SIFT descriptor. The eigenvector is computed in the original color image and the mean values of the normalized color g and b in each subregion are chosen to be the factors of the eigenvector. Compared with the SIFT descriptor, this descriptor's dimension has been reduced evidently, which can simplify the point matching process. The performance of the method is analyzed in theory in this paper and the experimental results have certified its validity too.
In this paper a coarse region segmentation of liver cancer in ultrasound images is introduced. The reason employing coarse region segmentation is to reflect the inhomogeneous distribution of the image gray levels and ...
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ISBN:
(纸本)9780819469533
In this paper a coarse region segmentation of liver cancer in ultrasound images is introduced. The reason employing coarse region segmentation is to reflect the inhomogeneous distribution of the image gray levels and provide the features such as the distribution, shape and size of the suspect region of liver cancer. Then combine with the prior knowledge we can divide the image into three different classes, which the results of the analysis of the region's location can be used by a classifier in a multilayer classifier. Furthermore, the result of the coarse region segmentation will support the texture analysis for further classification. The segmentation is based on watershed algorithm in order to receive an integrated region and two processing techniques are adopted to avoid the over segmentation of watershed algorithm.
In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for im...
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ISBN:
(纸本)9780819469519
In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for image fusion. Each image from different sensors could be decomposed into a low frequency image and a series of high frequency images of different directions by multi-sacle NSCT. For low and high frequency images, they are fused based on local-contrast enhancement and definition respectively. Finally, fused image is reconstructed from low and high frequency fused images. Experiment demonstrates that NSCT could preserve edge significantly and the fusion rule based on region segmentation performances well in local-contrast enhancement.
To obtain 3D ultrasound image, traditionally, a ID ultrasound transducer and an orientation system are used to get a series of 2D images and their positions. From these 2D images and position information, a 3D image i...
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ISBN:
(纸本)9780819466273
To obtain 3D ultrasound image, traditionally, a ID ultrasound transducer and an orientation system are used to get a series of 2D images and their positions. From these 2D images and position information, a 3D image is reconstructed. In this paper, the accuracy of the 3D image is determined by the accuracy of the position information, furthermore it affects the result of the measure from the 3D image. When in rotational scanning mode, the reconstructed 3D image is sensitive to the calibration parameters, including the orientation difference as well as the offset between the central line of each 2D US image and the rotational axis. To address this type of effects, we developed a 3D reconstruction technique considering the calibration uncertainty by building a transformation model with a 360 degrees scanning, and an accurate 3D reconstruction with calibration uncertainty is achieved. The experiments with both synthetic and scanning phantom data demonstrated the feasibility of our approach.
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