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Medical Image Dynamic Collaborative Processing on the Distributed Environment
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作者 张全海 Shi Pengfei 《High Technology Letters》 EI CAS 2003年第1期51-57,共7页
A new trend in the development of medical image processing systems is to enhance the sharing of medical resources and the collaborative processing of medical specialists. This paper presents an architecture of medical... A new trend in the development of medical image processing systems is to enhance the sharing of medical resources and the collaborative processing of medical specialists. This paper presents an architecture of medical image dynamic collaborative processing on the distributed environment by combining the JAVA, CORBA (Common Object Request and Broker Architecture) and the MAS (Multi-Agents System) collaborative mechanism. The architecture allows medical specialists or applications to share records and communicate with each other on the web by overcoming the shortcut of traditional approach using Common Gateway Interface (CGI) and client/server architecture, and can support the remote heterogeneous systems collaboration. The new approach improves the collaborative processing of medical data and applications and is able to enhance the interoperation among heterogeneous system. Research on the system will help the collaboration and cooperation among medical application systems distributed on the web, thus supply high quality medical service such as diagnosis and therapy to practicing specialists regardless of their actual geographic location. 展开更多
关键词 医学图像 图象处理 分布式系统 多AGENT 动态协作处理 WEB计算
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Watershed-based Image Segmentation with Region Merging and Edge Detection 被引量:1
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作者 Salman N H 《High Technology Letters》 EI CAS 2003年第1期58-63,共6页
The clustering technique is used to examine each pixel in the image which assigned to one of the clusters depending on the minimum distance to obtain primary classified image into different intensity regions. A waters... The clustering technique is used to examine each pixel in the image which assigned to one of the clusters depending on the minimum distance to obtain primary classified image into different intensity regions. A watershed transformation technique is then employes. This includes: gradient of the classified image, dividing the image into markers, checking the Marker Image to see if it has zero points (watershed lines). The watershed lines are then deleted in the Marker Image created by watershed algorithm. A Region Adjacency Graph (RAG) and Region Adjacency Boundary (RAB) are created between two regions from Marker Image. Finally region merging is done according to region average intensity and two edge strengths (T1, T2). The approach of the authors is tested on remote sensing and brain MR medical images. The final segmentation result is one closed boundary per actual region in the image. 展开更多
关键词 医学图像 脑图像 分水岭 图象分割 边缘检测 区域合并
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Hand Gesture Recognition Based on Improved FRNN 被引量:1
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作者 滕晓龙 王向阳 刘重庆 《Journal of Donghua University(English Edition)》 EI CAS 2005年第5期47-52,共6页
The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation opera... The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation operation. To solve the problem of hand gesture recognition, Fuzzy-Rough based nearest neighbour (FRNN) algorithm is applied for classification. For avoiding the costly compute, an improved nearest neighbour classification algorithm based on fuzzy-rough set theory (FRNNC) is proposed. The algorithm employs the represented cluster points instead of the whole training samples, and takes the hand gesture data's fuzziness and the roughness into account, so the compute spending is decreased and the recognition rate is increased. The 30 gestures in Chinese sign language alphabet are used for approving the effectiveness of the proposed algorithm. The recognition rate is 94.96%, which is better than that of KNN (K nearest neighbor)and Fuzzy-KNN (Fuzzy K nearest neighbor). 展开更多
关键词 模糊粗糙集 FRNN 手势识别 人工智能
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A universal method for camera calibration in UITS scenes
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作者 陈兆学 施鹏飞 《Chinese Optics Letters》 SCIE EI CAS CSCD 2005年第2期69-72,共4页
A universal approach to camera calibration based on features of some representative lines on traffic ground is presented. It uses only a set of three parallel edges with known intervals and one of their intersected li... A universal approach to camera calibration based on features of some representative lines on traffic ground is presented. It uses only a set of three parallel edges with known intervals and one of their intersected lines with known slope to gain the focal length and orientation parameters of a camera. A set of equations that computes related camera parameters has been derived from geometric properties of the calibration pattern. With accurate analytical implementation, precision of the approach is only decided by accuracy of the calibration target selecting. Final experimental results have showed its validity by a snapshot from real automatic visual traffic surveillance (AVTS) scencs. 展开更多
关键词 LINE A universal method for camera calibration in UITS scenes
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