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As the rolling machinery is the most important parts of mechanical systems, and the rolling components are playing a crucial role in mechanical transmission, so the fault diagnosis of rolling bearings are very important and valuable research object. During long time abrasion and harsh work conditions, the corrosion, crash, system fault, can easily lead the rolling components broken down, especially...
Most object classification models considered in image only exist positive samples and negative samples. In this paper, another type of sample exists, named “gray sample”, which belongs to neither positive samples nor negative samples, contains knowledge in other domains or scenes. The degree of “gray” is defined by semantic similarity between annotations and scenes. While the local descriptors represent...
Image saliency attempts to describe the most conspicuous part in an input image by mimicking human visual selective attention mechanism. Naturally, it could be adopted for improving object recognition. To demonstrate the effectiveness of saliency in object recognition, this paper proposes a salient hierarchical model. First, the traditional saliency model is modified for more robust saliency estimation...
In this paper, we propose the directional neighborhood distance and all-directional neighborhood distance (ADND) to measure the gray value variation between pixels in specific and all direction. The all-directional neighborhood distance is used to fuse multi-source images, and our experiments show that the proposed fusion method is effective in term of some objective evaluation indexes, such as spatial...
Making recognition more reliable under uncontrolled lighting conditions is one of the most important challenges for face recognition. In this correspondence, multi-scale illumination invariant is derived from the image gradient domain (MGI) which can discover underlying inherent structure while keeping the details at most. The resulting method provides state-of-the-art performance on two data sets...
To overcome the limitation of numeric feature description of software modules in Software defect prediction, we propose a novel module description technology, which employs the classifying feature, rather than numerical feature to describe the software module. Firstly, we construct independent classifier on each software metric. Then the classifying results in each feature are used to represent every...
In view of the over- and under-segmentation problems existed in the conventional image segmentation based on rough-set theory, an novel color image segmentation approach based on Rough-Set theory is presented in this paper. Firstly, the new distance has been defined by using the vector angle and Euclidean distance. And then according to the new distance, the space binary matrixes that represent the...
The traditional CBIR is sequential retrieval. However, for large and high-dimension image databases, it is obvious that this retrieval method has been unable to meet efficiency. It is more important that the image database should be preprocessed and establish indexing to improve retrieval efficiency. Focus on the hierarchical clustering algorithm's high computational complexity, this paper introduces...
Hidden Markov tree (HMT) is a tree-structure statistical model, which is used to capture the statistical structure information of smooth and singular regions. It works by modeling the relationship between the wavelet coefficients interscales. For the discrete wavelet transform (DWT) has its own drawbacks inherently, such as shift variance, lack of directionality, etc. The traditional HMT model based...
In order to enhance the accuracy of Chinese off-line handwriting recognition, a new method based on the pyramidal dual-tree directional filter bank (PDTDFB) was presented. According to multi-resolution, arbitrarily high direction resolution, low redundant ratio and efficient implementation properties, the PDTDFB transform can effectively capture more edges and contours in image. Using the extracting...
A novel first-detect-then-identify approach with SIFT features and discrete wavelet transform for tracking object is proposed in real surveillance scenarios. For accurate and fast moving object detection, discrete wavelet transform is adopted to eliminate the noises of the frames which may cause detection errors, and then objects are detected by applying the inter-frame difference method on the low...
Handwriting-based writer identification is a hot research filed in pattern recognition. Off-line text-independent writer identification still remains as a challenging problem because writing features can only be extracted from the handwriting images. As a result, plenty of dynamic writing information, which is very valuable for writer identification, is unavailable for off-line writer identification...
Both support vector machines (SVMs) and multi-resolution analysis (MRA) have been developed for solving signal approximation problem. When the scale function of MRA is adopted to act as the map function of SVMs, the high dimensional feature space in SVMs and the scale subspace in MRA will be the same Reproducing Kernel Hilbert Spaces (RKHS). Based on the fact, this paper proposes an algorithm for...
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