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李银桥 《数码设计:surface》2012,(3):110-112
图案是构成服装风格特征及其文化内涵的重要元素符号,彝族服饰图案纹饰丰富,形制各异,其美学意蕴源远流长。本文基于彝族服饰图案的美学特质,探讨彝族服饰图案在现代服装设计中的应用方法,从而为民族服饰图案在现代服装设计中的沿承和发展提供理论指导。 相似文献
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窦筱 《数码设计:surface》2012,(9):153-155
高密剪纸、扑灰年画、泥塑在产生与发展的过程中,它们的艺术特色随着不断的发展变化形成各自的艺术特点。 相似文献
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标准正面人脸图像的识别 总被引:7,自引:0,他引:7
本论文选用人脸上27个特殊点作为人脸基本特征。以人脸几何结构为基础,结合有脸识别的心理特性,提出新颖、简便、高精度的“寻找存在”法,使提取特征点的速度、精度得到大大的提高,在详细分析这27个特列点的统计特性后,选择了其中信息量丰富的15个点间距及间距比构成一组向量代替人脸描述,用加权欧氏距离作为特征向量间相似性测试,在两类实验中,识别率高达100%和98%。 相似文献
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Tuan D. Pham Dinh T.P. Le Jinwei Xu Duc T. Nguyen Robert G. Martindale Clifford W. Deveney 《Computer methods and programs in biomedicine》2014
An abdominal wall hernia is a protrusion of the intestine through an opening or area of weakness in the abdominal wall. Correct pre-operative identification of abdominal wall hernia meshes could help surgeons adjust the surgical plan to meet the expected difficulty and morbidity of operating through or removing the previous mesh. First, we present herein for the first time the application of image analysis for automated identification of hernia meshes. Second, we discuss the novel development of a new entropy-based image texture feature using geostatistics and indicator kriging. Third, we seek to enhance the hernia mesh identification by combining the new texture feature with the gray-level co-occurrence matrix feature of the image. The two features can characterize complementary information of anatomic details of the abdominal hernia wall and its mesh on computed tomography. Experimental results have demonstrated the effectiveness of the proposed study. The new computational tool has potential for personalized mesh identification which can assist surgeons in the diagnosis and repair of complex abdominal wall hernias. 相似文献
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《Expert systems with applications》2014,41(7):3333-3342
Early and accurate diagnosis of Parkinson’s disease (PD) is important for early management, proper prognostication and for initiating neuroprotective therapies once they become available. Recent neuroimaging techniques such as dopaminergic imaging using single photon emission computed tomography (SPECT) with 123I-Ioflupane (DaTSCAN) have shown to detect even early stages of the disease. In this paper, we use the striatal binding ratio (SBR) values that are calculated from the 123I-Ioflupane SPECT scans (as obtained from the Parkinson’s progression markers initiative (PPMI) database) for developing automatic classification and prediction/prognostic models for early PD. We used support vector machine (SVM) and logistic regression in the model building process. We observe that the SVM classifier with RBF kernel produced a high accuracy of more than 96% in classifying subjects into early PD and healthy normal; and the logistic model for estimating the risk of PD also produced high degree of fitting with statistical significance indicating its usefulness in PD risk estimation. Hence, we infer that such models have the potential to aid the clinicians in the PD diagnostic process. 相似文献
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《Expert systems with applications》2014,41(14):6131-6137
Face recognition demonstrates the significant progress in the research field of biometric and computer vision. The fact is due to the current systems perform well under relatively control environments but tend to suffer when the present of variation in pose, illumination, and facial expression. In this work, a novel approach for face recognition called Symmetric Local Graph Structure (SLGS) is presented based on the Local Graph Structure (LGS). Each pixel is represented with a graph structure of its neighbours’ pixels. The histograms of the SLGS were used for recognition by using the nearest neighbour classifiers that include Euclidean distance, correlation coefficient and chi-square distance measures. AT&T and Yale face databases were used to be experimented with the proposed method. Extensive experiments on the face database clearly showed the superiority of the proposed approach over Local Binary Pattern (LBP) and LGS. The proposed SLGS is robust to variation in term of facial expressions, facial details, and illumination. Due to good performance of SLGS, it is expected that SLGS has a potential for application implementation in computer vision. 相似文献
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王迪 《电脑与微电子技术》2014,(9):18-22
寄生虫病是危害人类及动物健康的疾病之一。为了实现对寄生虫卵的自动识别,辅助临床检测,提出基于线性判别分析的寄生虫卵识别方法。采用结合形态学滤波和Otsu的方法分割得到寄生虫卵及其轮廓,提取形状特征和纹理特征作为特征向量集,并利用线性判别分析实现对寄生虫卵自动识别。实验结果表明,该方法对6种寄生虫卵的识别正确率达到90.70%。 相似文献
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