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Recent advances in salient object detection in images have achieved obvious performance in various multimedia applications, but efficient salient object detection in videos is still a challenging problem. In this paper, we propose a novel salient object detection method based on spatio-temporal difference and coherence of video content. Firstly, we initialize the saliency map for each keyframe based...
This paper presents an optimized descriptor method for multispectral images. The method proposed is based on LGHD (Log-Gabor Histogram Descriptor)[1]. Initially, all feature points are detected from Long wave Infrared and Visible spectrum images, and descripted by LGHD, then PCA (Principal Component Analysis) is used to reduce the dimension of the two different descriptors, finally the optimized descriptors...
Feature extraction is at the core of satellite scene classification task. In this paper, we propose a fast binary coding (FBC) method to effectively generate the global discriminative feature representation of image scenes. Equipped with unsupervised feature learning technique, we first learn a set of optimal “filters” from large quantities of randomly sampled image patches, and then we obtain feature...
The paper presents Echo State Network (ESN) as classifier to diagnose the abnormalities in mammogram images. Abnormalities in mammograms can be of different types. An efficient system which can handle these abnormalities and draw correct diagnosis is vital. We experimented with wavelet and Local Energy based Shape Histogram (LESH) features combined with Echo State Network classifier. The suggested...
This paper presents a novel approach for real-time skin detection. The proposed approach enables reliable skin detection in dynamically changing illumination and environmental conditions. Histograms are used to model the color distributions in the approach, and they are estimated and dynamically updated by Kalman filters (KFs) over time. In addition, the illumination condition is estimated during...
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