Moving object segmentation is an important step toward development of any computer vision systems. In the present work, we have proposed a new method for segmentation of moving objects, which is based on single change...
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ISBN:
(纸本)9781467357593
Moving object segmentation is an important step toward development of any computer vision systems. In the present work, we have proposed a new method for segmentation of moving objects, which is based on single change detection method applied on Contourlet coefficients of two consecutive frames. We have chosen contourlet transform as it has high directionality and represents salient features of image such as edges, curves and contours in better way as compared with wavelet transform. The proposed method is simple and does not require any other parameter except contourlet coefficients. Results after applying the proposed method for segmentation of moving objects are compared with other state-of-the-art methods in terms of visual as well as quantitative performance measures viz. Average difference, Normalized absolute error and Pixel classification based measure. The proposed method is found to be better than other methods.
The objective of image fusion is to combine relevant information from two or more images of the same scene into a single composite image which is more informative and is more suitable for human and machine perception....
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ISBN:
(纸本)9781467357593
The objective of image fusion is to combine relevant information from two or more images of the same scene into a single composite image which is more informative and is more suitable for human and machine perception. In recent past, different methods of image fusion have been proposed in literature both in spatial domain and wavelet domain. Spatial domain based methods produce spatial distortions in the fused image. Spatial domain distortion can be well handled by the use of wavelet transform based image fusion methods. In this paper, we propose a pixel-level image fusion scheme using multiresolution Biorthogonal wavelet transform (BWT). Wavelet coefficients at different decomposion levels are fused using absolute maximum fusion rule. Two important properties wavelet symmetry and linear phase of BWT have been exploited for image fusion because they are capable to preserve edge information and hence reducing the distortions in the fused image. The performance of the proposed method have been extensively tested on several pairs of multifocus and multimodal images both free from any noise and in presence of additive white Gaussian noise and compared visually and quantitatively against existing spatial domain methods. Experimental results show that the proposed method improves fusion quality by reducing loss of significant information available in individual images. Fusion factor, entropy and standard deviation are used as quantitative quality measures of the fused image.
Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. In this paper, we propose a new video coding algorithm based on Distributed Compressive Sampling(DCS) principles, where almost...
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Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. In this paper, we propose a new video coding algorithm based on Distributed Compressive Sampling(DCS) principles, where almost all computation burdens can be shifted to the decoder, resulting in a very lowcomplexity encoder. At the decoder, compressed video can be efficiently reconstructed. Our algorithm can be useful in those video applications that require very low complex encoders. Simulation results show that our scheme compares favorably with existing schemes at a much lower implementation cost.
Colourisation is a kind of computer-aided technology which automatically adds colours to greyscale images. This paper presents a scribble-based colourisation method which treats the flat and edge pixels differently. F...
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In his paper, Prof. Ye Dongyi pointed out that the reduction approach introduced by Hu Xiaohua etc. will give wrong result in some situation. In this paper we come to a conclusion by analysis that the reduction approa...
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In recent years, research in automatic Sign Language Recognition (SLR) has undergone significant progress, serving as a founda-tional base for developing applications that aim to promote the integration of deaf indivi...
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Detecting interaction groups is an essential task for understanding human behaviours and social activities. However, it is still challenging to identify social interactions and the resulting crowd groups using purely ...
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A new scheme of object tracking with mean shift is put forward in this paper. At first, texture feature is fused in the processing by Local Ternary Pattern (LTP). Since LTP is sensitive to local noise, least median of...
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ISBN:
(纸本)9781467321969
A new scheme of object tracking with mean shift is put forward in this paper. At first, texture feature is fused in the processing by Local Ternary Pattern (LTP). Since LTP is sensitive to local noise, least median of squares (LMedS) algorithm is used to adaptively calculate the noise threshold for accurate estimation of the LTP texture information. Furthermore, target scale and orientation is estimated in case of partial occlusion or rotation, so as to realize robust object tracking. Experimental results show that the proposed algorithm can acquire robust tracking performance under complex background .
Compressive sensing (CS) is a new technique for data sampling and compression simultaneously. In this paper, we propose a novel distributed video coding algorithm with dynamic measurement rate allocation based on comp...
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Compressive sensing (CS) is a new technique for data sampling and compression simultaneously. In this paper, we propose a novel distributed video coding algorithm with dynamic measurement rate allocation based on compressive sensing principles, where almost all computation burdens can be shifted to the decoder, resulting in a very low-complexity encoder. So the proposed algorithm can be useful in those video applications that require very low complex encoders. At the decoder, the compressed video can be efficiently reconstructed with adaptive dictionary learning. The simulation results show that the proposed algorithm outperforms the distributed compressive video sensing with non-adaptive learning local dictionary and global dictionary.
This paper addresses an effective issue of content-based image retrieval (CBIR) by presenting Fuzzy Hamming Distance (FHD). Firstly, the theory of FHD is introduced, which includes degree of difference and cardinality...
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