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	Adaptive pixon represented segmentation (APRS) for 3D MR brain images based on mean shift and Markov random fields 期刊论文 OAI收割 PATTERN RECOGNITION LETTERS, 2011, 卷号: 32, 期号: 7, 页码: 1036-1043 作者: Lin, Lei; Garcia-Lorenzo, Daniel; Li, Chong; Jiang, Tianzi; Barillot, Christian 收藏 \| 浏览/下载：31/0 \| 提交时间：2015/08/12 MRI segmentation Markov random field Adaptive mean shift Pixon-representation EM algorithm
	自发荧光图像分割算法的研究学位论文 OAI收割工学硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2010 常志军收藏 \| 浏览/下载：69/0 \| 提交时间：2015/09/02 自发荧光成像图像处理医学图像分割直方图自适应分割算法 bioluminescence imaging image processing medical image segmentation histogram adaptive segmentation algorithm
	Adaptive deformation estimation of moving target by weight image analysis (EI CONFERENCE) 会议论文 OAI收割 2010 2nd International Conference on Future Computer and Communication, ICFCC 2010, May 21, 2010 - May 24, 2010, Wuhan, China Bai X.-G.; Dai M. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 An algorithm based on weight image analysis is proposed for adaptive deformation estimation of moving target in mean-shift tracking method. At the first we get the weight image from the target candidate region. Then we analyze the differences between the object and background. According to that the area estimation of the target can be converted into the image segmentation task. To realize the adaptive segmentation and estimation we define the threshold as the maximum variance between object and background. Combining the estimated area and covariance matrix we can estimate the width height and orientation of the object. The experimental results on three representative video sequences validate its robustness to the deformable estimation of the targets. 2010 IEEE.
	Adaptive segmentation algorithm for ship target under complex background (EI CONFERENCE) 会议论文 OAI收割 2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China Wang A.-B.; Wang C.-X.; Su W.-X.; Dong Y.-F. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 Segmentation of ship target under complex background has important research significance in long-range ship tracking and identification and an adaptive segmentation algorithm is proposed according to background images with different complexity. Local complexity of image is first calculated in this algorithm and then the original image is preprocessed with different de noising methods according to local complexity finally the image is binarized based on local complexity and the target is segmented. The experiment results indicate that the algorithm is adaptive and can meet the requirements of real-time processing which lays a foundation for ship target detection under complex background. 2010 IEEE.
	Adaptive Image Segmentation based on Fast Thresholding and Image Merging (EI CONFERENCE) 会议论文 OAI收割 16th International Conference on Artificial Reality and Telexistence - Workshops, ICAT 2006, November 29, 2006 - December 1, 2006, Hangzhou, China 作者: Zhang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：14/0 \| 提交时间：2013/03/25 Image segmentation is the first essential and important step of low level vision. This paper proposes a novel algorithm for adaptive image segmentation it can be applied in many conditions based on thresholding technique and segments merging according to their characteristics combine with spatial position. Our earlier work of getting the entire information of the histogram could help choose the multiple thresholds. However including complex target segmented. We describe the algorithm in detail and perform simulation experiments. The computation based on pixels can fully parallel processing to save time. 2006 IEEE. not all the peaks of the histogram correspond to obvious structural unit in the image. Spatial information must be involved. This paper also suggests subjoining segments matching for video image tracking. They will give great help to image segmentation. The proposed algorithm can meet the real-time requirement and lead to higher segmentation accuracy some types of texture can also be segmented well