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Detecting infrared pedestrian in outdoor smart video surveillance is always a challenging and difficult problem. Although there have been many methods based on histograms of oriented gradients (HOG) to solve this problem, they would probably fail because of shelter and poor quality of image. To overcome this problem, we propose a robust feature to describe pedestrian which is called entropy-edge weighted...
Developing segmentation techniques for overlapping cells has become a major hurdle for automated analysis of cervical cells. In this paper, an automated three-stage segmentation approach to segment the nucleus and cytoplasm of each overlapping cell is described. First, superpixel clustering is conducted to segment the image into small coherent clusters that are used to generate a refined superpixel...
Recent research in computer vision has shown that combining multiple features is an effective way to improve classification performance. Furthermore, the use of filters that convolve images at multiple filter responses can increase descriptions to images. The more distinctive the filter responses, the better it able to distinguish characteristics from other groups. Thus, this paper describes a combination...
Medical Image Retrieval and Classification is very important in Computer-Aided Diagnosis. Feature extraction is one of the most important techniques in content based image retrieval and classification. How to extract low-level features which reflect high-level semantics of an image is crucial for medical image retrieval and classification. In allusion to this issue, there proposed a method using edge...
Gray Scale Kernel has been recently introduced for image recognition tasks. The kernel is proved to be positive definite and thus can be used in Support Vector Machine (SVM) based recognition. In this paper, Profile Histogram Intersection (PHI) kernels, Detail Histogram Intersection (DHI) kernels and Susan Detail Histogram Intersection (SDHI) kernel function are proposed which based on traditional...
In this paper SVM algorithm is applied to classify the scenery video types in compressed domain. Firstly we extract video sequences randomly from scenery video and detect representative frames from the video sequences; secondly we extract features such as color layout, dominant color, edge histogram and face feature; then according to SVM, representative frames are classified as natural scenery, personality,...
Multiple kernel learning (MKL) approach for selecting and combining different representations of a data is presented. Selection of features from a representation of data using the MKL approach is also addressed. A base kernel function is used for each representation as well as for each feature from a representation. A new kernel is obtained as a linear combination of base kernels, weighted according...
As a basic two-class classifier, support vector machine (SVM) has been proved to perform well in image classification, which is one of the most common tasks of image processing. However, for the n-class problem in image classification, SVM treats it as n two-class problems, in this way, unclassifiable regions exist. In this paper, we introduce fuzzy support vector machine (FSVM) and define a membership...
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