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The current focus of our research is to detect and classify the plant disease in agricultural domain, by implementing image processing techniques. We aim to propose an innovative set of statistical texture features for classification of plant diseases images of leaves. The input images are taken by various mobile cameras. The Scale-invariant feature transform (SIFT) features used as texture feature...
Action recognition has been an active research area in computer vision community during the recent years. However, it is still a challenging task due to the difficulties mainly resulted from the background clutter, illumination changes, large intra-class variation and noise. In this paper, we aim to develop an action recognition approach by navigating focus of attention (action region) with saliency...
Action recognition has been a growing research topic in computer vision due to its great potentials for real-world applications. In this paper, we develop an effective action recognition approach based on salient object detection and propose a new feature descriptor to represent the changes of edge orientation. Firstly, we detect salient objects from each frame of a video sequence and generate edge...
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