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In this paper, we study the normalized measure of audio scrambling degree which is consistent with the human auditory system. Firstly, we study the average short term audio entropy property. Randomly selecting consecutive sample points from a given-length audio analysis frame, we compute its short term entropy and then its corresponding mean value. With the increasing length for an analysis frame,...
In this paper, We present a novel segmentation technique which is based on Grey relational analysis of Grey system theory. According to global and local inter-pixel correlation, we can extract region of interest from original images. The experimental results show that our algorithms can effectively extract the target area, and has strong anti-noise capability, this new method is simple, fast, and...
With the development of image compress technology, video is used more and more often. For the complexity of the subjective video quality estimation, many researchers are pay attention to the objective video quality assessment. In this paper, we proposed a color video quality assessment based on edge-color distortion. First, the edge and the color distortion models are introduced. Then, the response...
Measurement of visual quality is of fundamental importance for numerous video processing applications. In this paper, we proposed a full-reference color video quality assessment based on quaternion singular value decomposition(QSVD), which takes into account the luminance, chrominance and gradient information of each pixel and treats them as a whole. The algorithm is tested on the video quality experts...
Most proposed video quality assessment approaches in the literature are only applied to the luminance layer of frame. Others are applied to luminance and chrominance layers respectively and then pooling by means of grayscale image quality metrics. In this paper, we proposed a full-reference objective video quality assessment called CMSVD,which treats luminance and chrominance parts as a whole and...
Spatiograms were generalization of histograms, which can harvest spatial information of images. The similarity measure is important when applying spatiograms to various computer vision problems such as tracking and image retrieval. The original proposed measures use Mahalanobis distance of coordinate mean to measure spatial information in spatiograms. However, spatial information which is described...
When trying to discover knowledge on a collection of data, one of the first arising tasks is to identify groups of similar objects, that is, to carry out cluster analysis for obtaining data partitions. Thus, a decision must be taken for choosing the clustering result that produces the best data partition for a given data collection. In order to support such a decision, indexes for measuring the quality...
Speedy and reliable face location is a key for monitoring driver fatigue driving condition using machine vision methods. According to the disadvantage of face location methods based on single feature in accuracy and reliability at present, first, an improved face location method based on Haar-like feature and Adaboost is used to detect the possibly existing face region in the whole image, then the...
Zhou Wang proposed the Structural Similarity theory (MSSIM), Guan-Hao Chen proposed a marginal texture distorts theory on it. Jian-Xin Pang proposed a method of image quality assessment based on the energy of structural distortion (ESD). Because the theory isn't applied directly on the video field and it don't think over HVS. So we propose a method of video quality assessment based on the sensitive...
For the binocular vision system based on light-weighted passive IR reflective markers and IR LED array PCB board, which is used to measure the 3-D motion parameters of rocket motor, the most important issue is determining the coordinates of infrared markers. In order to solve this problem, a fast center of mass estimation algorithm was proposed in this paper. The new algorithm segments the infrared...
We address the problem of feature weight learning for image clustering. In practice, before clustering data, we generally normalize all data features between 0 and 1, because we cannot determine which features are more important. In this paper, we provide a feature weight learning framework for clustering which can obtain the feature weights and cluster labels simultaneously. An alternative optimization...
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