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We propose a novel contrast enhancement method for dark images using the value gap expansion force (VGEF) and the sorted histogram equalization. Based on the observation that the inter-pixel relationship is analogous to the electrostatic force, we define the pixel field spread around each pixel and the pixel mass at each pixel position. We compute the VGEF exerted to a pixel by multiplying the pixel...
A video genre classification algorithm based on the voting from multiple SVMs is proposed in this work. While conventional genre classifiers use generic baseline features, we employ more specialized features to describe five video genres: animation, commercial, entertainment, drama, and sports. We also present a robust classification algorithm using multiple SVMs, which consider all possible binary...
In this paper, a hybrid approach incorporating the Nearest Shrunken Centroid (NSC) and Genetic Algorithm (GA) is proposed to automatically search for an optimal range of shrinkage threshold values for the NSC to improve feature selection and classification accuracy for high dimensional data. The selection of a threshold value is crucial as it is the key factor in the NSC to find significant relative...
In this paper, a new approach is proposed for feature reduction using a GA-Rough hybrid approach on Bio-medical data. The given set of bio-medical data is pre-processed with the min-max normalization method. Then the subsequent evaluation on each feature with respect to the output class is carried out utilizing the information gain-based approach using the entropy-based discretization. Features with...
An efficient colorization scheme for images and videos based on prioritized source propagation is proposed in this work. A user first scribbles colors on a set of source pixels in an image or the first frame of a movie. The proposed algorithm then propagates those colors to the other non-source pixels and the subsequent frames. Specifically, the proposed algorithm identifies the non-source pixel with...
It has been shown that the rate of preterm birth in remote and rural populations in Australia is more than twice of those in the metropolitan population, and that increased access to quality antenatal care in such communities leads to a significant improvement. This paper describes a system that supports remote fetal heart rate monitoring, thus providing a technique that addresses this need for better...
Support vector machines (SVM) can overcome the disadvantage of traditional anomaly detection, which need large sample data and have great effect in real-time detection, but has the disadvantage of slow training velocity. Least squares support vector machines (LS-SVM) can overcome the disadvantage of slow training velocity, but makes the solution lose sparsity and robustness. So a weighted LS-SVM (WLS-SVM)...
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