In this paper, we present a software-based noninvasive system to implement binocular stereo vision with the help of polarized glass or other auxiliary equipments. For any application based on OpenGL, our system can gi...
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Statistical distribution fitting and regression fitting are both classic methods to model data. There are slight connections and differences between them, as a result they outperform each other in different cases. A a...
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Recently, a new representation for recognizing instances and categories of scenes called spatial Principal component analysis of Census Transform histograms (PACT) has shown its excellent performance in the scene imag...
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In this paper, we propose a new method to improve the image registration accuracy in feedforward neural networks (FNN) based scheme. In the proposed method, Bayesian regularization is applied to improve the generaliza...
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In recent years, different Artificial Intelligence methods have been applied to pulsar search, such as Artificial Neural Network method, PEACE Sorting Algorithm, Real-time Classification method. In this paper, Weighti...
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In the study of object recognition, image texture segmentation has being a hot and difficult aspect in computer vision. Feature extraction and texture segmentation algorithm are two key steps in texture segmentation. ...
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Open-dose by reconstruction is one of the most important algorithms in mathematical morphology, it was used widely in image and video processing, but it requires the huge computational power, what is the bottleneck fo...
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Open-dose by reconstruction is one of the most important algorithms in mathematical morphology, it was used widely in image and video processing, but it requires the huge computational power, what is the bottleneck for application. So in this paper, Cellular Neural Network (CNN) is used to solve the problem, new +1 template and "and" template are designed here, along with the already developed templates and image preprocessing technique, the gray-scale open-close by reconstruction is realized. Experimental results based on CNN simulator are shown, proved that the speed on CNN is about 300 times faster than in traditional PC, the real time processing can be realized.
There is a considerable interest in designing automatic systems that will scan a given paper document and store it on electronic media for easier storage, manipulation, and access. Most documents contain graphics and ...
Deep convolution neural network (CNN) is one of the most popular Deep neural networks (DNN). It has won state-of-the-art performance in many computer vision tasks. The most used method to train DNN is Gradient descent...
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The license plate location technique is an important imageprocessing step in license plate recognition system. Vehicle license plates are distinguished from backgrounds using features proposed in existing literatures...
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The license plate location technique is an important imageprocessing step in license plate recognition system. Vehicle license plates are distinguished from backgrounds using features proposed in existing literatures. However, the effect of location is quite affected by feature selection. In this paper, we propose a method of precise license plate location fusing salient features. The method is mainly divided into three steps. First, candidate license plate regions are detected using improved Harris corner feature with much less time than traditional method. Then, candidates are sifted to only retain license plates based on two salient features named color combination and mean difference which are first proposed in this paper. Finally, the license plates are located precisely according to the projection feature. In experiment, the proposed algorithm was tested with 1942 real images captured in different environment and the license plates are successfully located as 97.6% in average with only 109ms. The experiment results demonstrates the effectiveness and efficient of our algorithm.
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