Corner detection is a chief step in computer vision. A new corner detection algorithm in planar curves is proposed. Firstly, from the human perception, two key characteristics are given as an amendment of the traditio...Corner detection is a chief step in computer vision. A new corner detection algorithm in planar curves is proposed. Firstly, from the human perception, two key characteristics are given as an amendment of the traditional corner properties. Based on the two properties, the concept of the fuzzy set is introduced into a detection. Secondly, the extracted-formulae of three groups including the features of the corner subject degree are derived. Through synthesizing the features of three groups, the judgments of the corner detection, location, and optimization are obtained. Finally, by using the algorithm the detection results of several examples and feature curves for some interested parts, as well as the detection results for the test images history in references are given. Results show that the algorithm is easily realized after adopting the fuzzy set, and the detection effect is very ideal.展开更多
Objective To explore the characteristics of cognitive impariment in ultra high-risk subjects and familial high risk group with schizophrenia.Methods The cognitive function was assessed by the Trail Marking Test,Symbol...Objective To explore the characteristics of cognitive impariment in ultra high-risk subjects and familial high risk group with schizophrenia.Methods The cognitive function was assessed by the Trail Marking Test,Symbol Coding(SC),Hopkins Verbal Learning Test-Revised(HVLT-R),Brief Visual spatial Memory展开更多
文摘Corner detection is a chief step in computer vision. A new corner detection algorithm in planar curves is proposed. Firstly, from the human perception, two key characteristics are given as an amendment of the traditional corner properties. Based on the two properties, the concept of the fuzzy set is introduced into a detection. Secondly, the extracted-formulae of three groups including the features of the corner subject degree are derived. Through synthesizing the features of three groups, the judgments of the corner detection, location, and optimization are obtained. Finally, by using the algorithm the detection results of several examples and feature curves for some interested parts, as well as the detection results for the test images history in references are given. Results show that the algorithm is easily realized after adopting the fuzzy set, and the detection effect is very ideal.
文摘Objective To explore the characteristics of cognitive impariment in ultra high-risk subjects and familial high risk group with schizophrenia.Methods The cognitive function was assessed by the Trail Marking Test,Symbol Coding(SC),Hopkins Verbal Learning Test-Revised(HVLT-R),Brief Visual spatial Memory
