尤新革
模式识别、图像处理、计算机视觉,信号处理、小波分析与时频分析。
个性化签名
- 姓名:尤新革
- 目前身份:
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学术头衔:
博士生导师, 教育部“新世纪优秀人才支持计划”入选者
- 职称:-
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学科领域:
模式识别
- 研究兴趣:模式识别、图像处理、计算机视觉,信号处理、小波分析与时频分析。
尤新革,1969年10月出生,教授。
学术兼职:美国电子电气工程学会会员(IEEE Member);《International Journal of Wavelets, Multiresolution and Information Processing》客座主编,《International Journal of Information Analysis and Processing》编委,IEEE Trans. on SMC, Pattern Recognition, Pattern Recognition Letters, International Journal of Pattern Recognition and Artificial Intelligence 特约评审。
经历:2004年3月香港浸会大学博士毕业。2004年7月至2007年3月,香港浸会大学博士后合作研究,期间访问了加拿大康可迪亚大学、日本旭化成研究中心和澳门大学,参与合作研究。
研究方向:模式识别、图像处理、计算机视觉,信号处理、小波分析与时频分析。
负责项目:[1] 主持国家自然科学基金“基于新小波的图形特征表示与提取”;[2] 主持湖北省自然科学基金“基于不可分小波的笔迹鉴别研究;[3] 主持湖北省自然科学基金“基于小波的生物特征提取与识别研究”;[4] 主持湖北省自然科学基金“基于新小波函数的图形特征提取”;[5] 主持武汉市青年科技晨光计划“基于小波的图形特征提取与智能识别的研究”。
研究成果:[1] 2005年获湖北省自然科学三等奖(第二完成人);[2] 2004年中港人工智能及应用与创意大赛,二等奖;[3] 近几年发表论文50余篇,SCI收录20余篇。
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【期刊论文】Wavelet-Based Approach to Character Skeleton
尤新革, Xinge You, Member, IEEE, and Yuan Yan Tang, Fellow
IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 16, NO.5, MAY 2007,-0001,():
-1年11月30日
Character skeleton plays a significant role in character recognition. The strokes of a character may consist of two regions, i.e., singular and regular regions. The intersections and junctions of the strokes belong to singular region, while the straight and smooth parts of the strokes are categorized to regular region. Therefore, a skeletonization method requires two different processes to treat the skeletons in theses two different regions. All traditional skeletonization algorithms are based on the symmetry analysis technique. The major problems of these methods are as follows. 1) The computation of the primary skeleton in the regular region is indirect, so that its implementation is sophisticated and costly. 2) The extracted skeleton cannot be exactly located on the central line of the stroke. 3) The captured skeleton in the singular region may be distorted by artifacts and branches. To overcome these problems, a novel scheme of extracting the skeleton of character based on wavelet transform is presented in this paper. This scheme consists of two main steps, namely: a) extraction of primary skeleton in the regular region and b) amendment processing of the primary skeletons and connection of them in the singular region. A direct technique is used in the first step, where a new wavelet-based symmetry analysis is developed for finding the central line of the stroke directly. A novel method called smooth interpolation is designed in the second step, where a smooth operation is applied to the primary skeleton, and, thereafter, the interpolation compensation technique is proposed to link the primary skeleton, so that the skeleton in the singular region can be produced. Experiments are conducted and positive results are achieved, which show that the proposed skeletonization scheme is applicable to not only binary image but also gray-level image, and the skeleton is robust against noise and affine transform.
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【期刊论文】SKELETONIZATION OF RIBBON-LIKE SHAPES WITH NEW WAVELET FUNCTION
尤新革, XIN-GE YOU (a, b), YUAN Y. TANG (b), LU SUN (b)
Proceedings of the First International Conference on Machine Learning and Cybernetics, Beijing, 4-5 November 2002,-0001,():
-1年11月30日
In this paper we propose a new scheme to extract skeleton of Ribbon-like shape with a novel wavelet function. It consists of two phases, namely: based on these perfect properties of new wavelet function, and symmetry analyses of maxima modaii of wavelet transform are given. Midpoints of all pairs of contour elements are connected to generate a skeleton of the Shape, which is defined as wavelet skeleton. Four basic criteria for modifying the artifacts of wavelet skeleton are presented. A corresponding algorithm is developed, and the experimental results are shown that this algorithm is capable of extracting exactly skeleton of Ribbon-like shape with different widths as well as different grey-levels.
Skeletonization, wavelet transform, wavelet skeleton, maximum moduli symmetry, wavelet gradient code
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