Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new meth...Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps:use computer and simulation software to build target object's virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors' sequence.The vectors' sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough.展开更多
Many websites use verification codes to prevent users from using the machine automatically to register,login,malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as ...Many websites use verification codes to prevent users from using the machine automatically to register,login,malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as entering the verification code manually.Improving the verification code security system needs the identification method as the corresponding testing system.We propose an anisotropic heat kernel equation group which can generate a heat source scale space during the kernel evolution based on infinite heat source axiom,design a multi-step anisotropic verification code identification algorithm which includes core procedure of building anisotropic heat kernel,settingwave energy information parameters,combing outverification codccharacters and corresponding peripheral procedure of gray scaling,binarizing,denoising,normalizing,segmenting and identifying,give out the detail criterion and parameter set.Actual test show the anisotropic heat kernel identification algorithm can be used on many kinds of verification code including text characters,mathematical,Chinese,voice,3D,programming,video,advertising,it has a higher rate of 25%and 50%than neural network and context matching algorithm separately for Yahoo site,49%and 60%for Captcha site,20%and 52%for Baidu site,60%and 65%for 3DTakers site,40%,and 51%.for MDP site.展开更多
The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we propose...The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we proposed a kernel regression-based method for joint multi-view space object recognition and pose estimation. We built a new simulated satellite image dataset named BUAA-SID 1.5 to test our method using different image representations. We evaluated our method for recognition-only tasks, pose estimation-only tasks, and joint recognition and pose estimation tasks. Experimental results show that our method outperforms the state-of-the-arts in space object recognition, and can recognize space objects and estimate their poses effectively and robustly against noise and lighting conditions.展开更多
基金Supported by the Ministerial Level Research Foundation(404040401)
文摘Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps:use computer and simulation software to build target object's virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors' sequence.The vectors' sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough.
基金The national natural science foundation(61273290,61373147)Xiamen Scientific Plan Project(2014S0048,3502Z20123037)+1 种基金Fujian Scientific Plan Project(2013HZ0004-1)FuJian provincial education office A-class project(-JA13238)
文摘Many websites use verification codes to prevent users from using the machine automatically to register,login,malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as entering the verification code manually.Improving the verification code security system needs the identification method as the corresponding testing system.We propose an anisotropic heat kernel equation group which can generate a heat source scale space during the kernel evolution based on infinite heat source axiom,design a multi-step anisotropic verification code identification algorithm which includes core procedure of building anisotropic heat kernel,settingwave energy information parameters,combing outverification codccharacters and corresponding peripheral procedure of gray scaling,binarizing,denoising,normalizing,segmenting and identifying,give out the detail criterion and parameter set.Actual test show the anisotropic heat kernel identification algorithm can be used on many kinds of verification code including text characters,mathematical,Chinese,voice,3D,programming,video,advertising,it has a higher rate of 25%and 50%than neural network and context matching algorithm separately for Yahoo site,49%and 60%for Captcha site,20%and 52%for Baidu site,60%and 65%for 3DTakers site,40%,and 51%.for MDP site.
基金co-supported by the National Natural Science Foundation of China (Grant Nos. 61371134, 61071137)the National Basic Research Program of China (No. 2010CB327900)
文摘The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we proposed a kernel regression-based method for joint multi-view space object recognition and pose estimation. We built a new simulated satellite image dataset named BUAA-SID 1.5 to test our method using different image representations. We evaluated our method for recognition-only tasks, pose estimation-only tasks, and joint recognition and pose estimation tasks. Experimental results show that our method outperforms the state-of-the-arts in space object recognition, and can recognize space objects and estimate their poses effectively and robustly against noise and lighting conditions.