Shape from shading(SFS)is an important domain in computer vision.The paper presented an improved algorithm of shape from shading based on a single image according to an existed one.The presented algorithm enhanced the...Shape from shading(SFS)is an important domain in computer vision.The paper presented an improved algorithm of shape from shading based on a single image according to an existed one.The presented algorithm enhanced the boundary constraints to eliminate the rotation distortion on the border of reconstructed object and introduced the factor of brightness error to weaken the influence irradiance equation’s nonlinearity on reconstructed errors.The reconstructed results verify the performance improvement in terms of accuracy by the input image of a synthetic image and a real image of weld.展开更多
Modeling is essential, significant and difficult for the quality and shaping control of arc welding process. A generalized rough set based modeling method was brought forward and a dynamic predictive model for pulsed ...Modeling is essential, significant and difficult for the quality and shaping control of arc welding process. A generalized rough set based modeling method was brought forward and a dynamic predictive model for pulsed gas tungsten arc welding (GTAW) was obtained by this modeling method. The results show that this modeling method can well acquire knowledge in welding and satisfy the real life application. In addition, the results of comparison between classic rough set model and back-propagation neural network model respectively are also satisfying.展开更多
基金National Natural Science Foundation ofChina(No.60 4740 3 6)
文摘Shape from shading(SFS)is an important domain in computer vision.The paper presented an improved algorithm of shape from shading based on a single image according to an existed one.The presented algorithm enhanced the boundary constraints to eliminate the rotation distortion on the border of reconstructed object and introduced the factor of brightness error to weaken the influence irradiance equation’s nonlinearity on reconstructed errors.The reconstructed results verify the performance improvement in terms of accuracy by the input image of a synthetic image and a real image of weld.
基金The National Natural Science Foundation of China(No 60474036)
文摘Modeling is essential, significant and difficult for the quality and shaping control of arc welding process. A generalized rough set based modeling method was brought forward and a dynamic predictive model for pulsed gas tungsten arc welding (GTAW) was obtained by this modeling method. The results show that this modeling method can well acquire knowledge in welding and satisfy the real life application. In addition, the results of comparison between classic rough set model and back-propagation neural network model respectively are also satisfying.
