This paper presents a two-layer threshold method for the corner detection. The method is inspired by the classical Susan corner detection model, and the improvement is two-fold. One is the choice of the self-adaptive ...
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Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectu...
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In this paper, we propose adaptive rectangular windows to improve object retrieval. The adaptive rectangular windows are created by G-means clusters, and solve the problem that G-means splits the database image into s...
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In this paper, we propose adaptive rectangular windows to improve object retrieval. The adaptive rectangular windows are created by G-means clusters, and solve the problem that G-means splits the database image into small irregular regions and decreases the retrieval accuracy. According to the spatial information in the clusters and the relative spatial relationship between the clusters, the rectangular windows adjust adaptively and represent the object regions with more spatial information. Afterwards, each adaptive rectangular window corresponds to an independent window vector, which increases the similarity between query object region and object regions of database images. The experimental results on the Oxford building dataset demonstrate that the adaptive rectangular windows improve the retrieval accuracy while ensuring the retrieval efficiency.
An effective dual-channel noise reduction algorithm is proposed based on sparse representations. The algorithm is composed of the following steps. Firstly, overlapping patches sampled from two channels together instea...
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An effective dual-channel noise reduction algorithm is proposed based on sparse representations. The algorithm is composed of the following steps. Firstly, overlapping patches sampled from two channels together instead of each channel one by one are trained to be a dictionary via K-SVD. Secondly, OMP(Orthogonal-Matching-Pursuit) reconstruction algorithm is applied to obtain the sparse coefficients of patches using the dictionary. Thirdly, the denoising speech can be obtained by the updated coefficients. Lastly, the above three steps are iterated to get clearer speech until some conditions are reached. Experimental results show that this algorithm performs better than that with single channel.
In order to solve the initial active contour problem of Snake model, Contourlet transform is introduced into the GVF Snake model, which will provides a way to set the initial contour, as a result, will improves the ed...
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Evolutionary data, such as topic changing blogs and evolving trading behaviors in capital market, is widely seen in business and social applications. The time factor and intrinsic change embedded in evolutionary data ...
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An adaptive filtering method based on the anisotropic diffusion equation is proposed in this paper. Firstly, the denoising principal of the anisotropic diffusion equation is studied. And then, adaptive filtering of im...
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Character information is hard to detect in billet scene images by CCD camera. In this paper, we present a method for detection of billet characters from measurements of recursive segmented image. This recursive segmen...
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Character information is hard to detect in billet scene images by CCD camera. In this paper, we present a method for detection of billet characters from measurements of recursive segmented image. This recursive segmented method can be used in a wide variety of billet scenes. According to high temperature and complex scene in the rolling line, we use an effective clustering and projection characteristics to determine the terminal condition of recursive segmentation. Then we can label character candidate regions in turn by this effective characteristics, and select the regions we want to achieve. The experiments show that this method makes full use of the characteristics of region and clustering. It can improve the quality of detection, and the detection result meets the need of practical application.
Aiming at the state estimation of nonlinear system in multi-sensor observation uncertainty, a novel cost reference particle filter algorithm based on consistency weight fusion is proposed in this paper. Firstly, the c...
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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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