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RISS 인기검색어
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- 저자 : ( Haolin Gao ) (검색결과 3 건)
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A Cluster Priority Level Decision Method for Image Features
Tianqiang Peng,Haolin Gao 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.2
Though clustering Analysis has been developed for many years with many clustering methods come into application, image clustering is still a difficult problem. One of the most fundamental problems is that there are many kinds of image representations, and the distinguish ability of each feature is different, so their cluster effects are also different. To decide cluster priority level of different images features on a specific image dataset, the distinguish ability of three typical image features are analyzed, and a cluster discriminant index is present, which called Simplified Overall Cluster Quality is composed of cluster compaction and cluster separation. Experimental results showed the feature with best distinguish ability also possessed best discriminant index. So this index can be used to decide the priority of features for clustering images or the best feature for image cluster.
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A Novel Video Image Text Detection Method
( Lin Zhou ),( Xijian Ping ),( Haolin Gao ),( Sen Xu ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.4
A novel and universal method of video image text detection is proposed. A coarse-to-fine text detection method is implemented. Firstly, the spectral clustering (SC) method is adopted to coarsely detect text regions based on the stationary wavelet transform (SWT). In order to make full use of the information, multi-parameters kernel function which combining the features similarity information and spatial adjacency information is employed in the SC method. Secondly, 28 dimension classifying features are proposed and support vector machine (SVM) is implemented to classify text regions with non-text regions. Experimental results on video images show the encouraging performance of the proposed algorithm and classifying features.
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A Novel Video Image Text Detection Method
( Lin Zhou ),( Xijian Ping ),( Haolin Gao ),( Sen Xu ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.3
A novel and universal method of video image text detection is proposed. A coarse-to-fine text detection method is implemented. Firstly, the spectral clustering (SC) method is adopted to coarsely detect text regions based on the stationary wavelet transform (SWT). In order to make full use of the information, multi-parameters kernel function which combining the features similarity information and spatial adjacency information is employed in the SC method. Secondly, 28 dimension classifying features are proposed and support vector machine (SVM) is implemented to classify text regions with non-text regions. Experimental results on video images show the encouraging performance of the proposed algorithm and classifying features.
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