SIA OpenIR  > 智能产线与系统研究室
Alternative TitleResearch on Electrical Symbols Recognition of HOG
刘剑; 龚志恒; 高恩阳; 刘亚楠
Source Publication沈阳建筑大学学报(自然科学版)
Contribution Rank3
Funding Organization国家自然科学基金项目(61272253);; 住房和城乡建设部科技项目(2010-K9-22)
Keyword电气符号识别 Hog特征 支持向量机 梯度直方图
Other AbstractElectrical symbols recognition is one of the hot spots in the field of computer vision and electrical design recently. Various factors will bring errors on computer recognition of electrical drawings, such as size of the electrical symbols, drawings of background fuzzy, rotation of the electrical symbols etc.. There are many electrical symbols recognition methods, but the problems are solved hardly. In order to overcome the external interference factors and improve recognition accuracy, an electrical symbol recognition method based on HOG is presented in the paper. Firstly, the electrical symbol training sets were established, and symbols of HOG feature were extracted. Secondly, support vector machine was trained by mean of these characteristics of HOG and classification information. Finally, symbols were recognized by support vector machines. Con- ducted different experiment of complex background research of electrical symbols and experimental study on the algorithm of the algorithm of SIFT and HOG, the results of experiments show that the proposed algorithm of HOG has good detection after experiment.
Document Type期刊论文
Recommended Citation
GB/T 7714
刘剑,龚志恒,高恩阳,等. 电气符号识别的HOG方法[J]. 沈阳建筑大学学报(自然科学版),2013,29(3):571-576.
APA 刘剑,龚志恒,高恩阳,&刘亚楠.(2013).电气符号识别的HOG方法.沈阳建筑大学学报(自然科学版),29(3),571-576.
MLA 刘剑,et al."电气符号识别的HOG方法".沈阳建筑大学学报(自然科学版) 29.3(2013):571-576.
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