image segmentation is a key technology to image analysis and processing. How to segment portrait fast and robust from the background is a difficult problem. With revising histogram segmentation by threshold in blue to...
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ISBN:
(纸本)9781932415643
image segmentation is a key technology to image analysis and processing. How to segment portrait fast and robust from the background is a difficult problem. With revising histogram segmentation by threshold in blue tone space, we present an adaptable quantum evolution threshold-searching algorithm to segment portrait fast and robust. Experiments and detail comparison analysis are provided to demonstrate effects.
This paper presents a level of detail (LOD) selection algorithm for multi-resolution volume rendering using 3D texture mapping. It uses an adaptive scheme that renders the volume in a region-of-interest at a high reso...
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In this paper, we propose a novel automatic object extraction algorithm, named the Template Guided Live Wire, based on the popularly used live-wire techniques. We discuss in details the novel method’s applications on...
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In this paper, we propose a novel automatic object extraction algorithm, named the Template Guided Live Wire, based on the popularly used live-wire techniques. We discuss in details the novel method’s applications on tongue extraction in digital images. With the guides of a given template curve which approximates the tongue’s shape, our method can finish the extraction of tongue without any human intervention. In the paper, we also discussed in details how the template guides the live wire, and why our method functions more effectively than other boundary based segmentation methods especially the snake algorithm. Experimental results on some tongue images are as well provided to show our method’s better accuracy and robustness than the snake algorithm.
The efficiency of an image compression technique relies on the capability of finding sparse M-terms for best approximation with reduced visually significant quality loss. By "visually significant" it is mean...
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This paper gives a robust motion detection and tracking solution for a video surveillance application on an airport's apron. As an outdoor application, the system must be capable of adapting to a wide range of wea...
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This paper gives a robust motion detection and tracking solution for a video surveillance application on an airport's apron. As an outdoor application, the system must be capable of adapting to a wide range of weather conditions and illumination changes. Furthermore, the achromaticity of the scene and the presence of occlusions in the tracking process are issues considered in the selection of the motion detector and tracking system respectively. We propose an adapted mixture of Gaussians model with RGB colour normalisation to detect mobile objects in the scene and a region tracking method based on significant mobile object features to track individuals and vehicles on the selected airport's apron. The performance of the proposed motion detector is evaluated using pixel-based performance metrics and compared with other existing methods. The capability of the application to handle partial occlusions is tested on the region tracker.
In this paper we construct a novel human body model using convolution surface with articulated kinematic skeleton. The human body's pose and shape in a monocular image can be estimated from convolution curve throu...
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Based on statistical learning theory, support vector machine (SVM) is a novel type of learning machine, and it contains polynomial, neural network and radial basis function (RBF) as special cases. The mapped least squ...
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Based on statistical learning theory, support vector machine (SVM) is a novel type of learning machine, and it contains polynomial, neural network and radial basis function (RBF) as special cases. The mapped least squares support vector machine (MLS-SVM) is a special least square SVM (LS-SVM), which extends the application of the SVM to the imageprocessing. Based on the MLS-SVM, a family of filters for the approximation of partial derivatives of the digital image surface is designed. Prior information (e.g., local dominant orientation) are incorporated in a two dimension weighted function. The weighted MLS-SVM with the radial basis function kernel is applied to design the proposed filters. Exemplary application of the proposed filters to fingerprint image segmentation is also presented.
This paper addresses the application of hand gesture recognition in monocular image sequences using Active Appearance Model (AAM). For this work, the proposed algorithm is conposed of constructing AAMs and fitting the...
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This paper addresses the application of hand gesture recognition in monocular image sequences using Active Appearance Model (AAM). For this work, the proposed algorithm is conposed of constructing AAMs and fitting the models to the interest region. In training stage, according to the manual labeled feature points, the relative AAM is constructed and the corresponding average feature is obtained. In recognition stage, the interesting hand gesture region is firstly segmented by skin and movement ***, the models are fitted to the image that includes the hand gesture, and the relative features are ***, the classification is done by comparing the extracted features and average features. 30 different gestures of Chinese sign language are applied for testing the effectiveness of the method. The Experimental results are given indicating good performance of the algorithm.
Based on the study of the characteristics of humans' vision system, this paper designed a new algorithm of medical image compression and combined the masking feature of human vision system and the three component ...
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Based on the study of the characteristics of humans' vision system, this paper designed a new algorithm of medical image compression and combined the masking feature of human vision system and the three component model of the image. The experiments were done on the medical images including CT and MRI. The results show that under the same compression ratio, the method used in the paper can achieve better subjective visual quality. The compression ratio can reach 16:1, if the visually lossless effect is required, i.e., almost all the relevant medical information is reserved.
Many vision-related processing tasks, including edge detection and image segmentation, can be performed more easily when all objects in the scene are in good focus. However, in practice, this may not be always feasibl...
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