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We propose a novel obstacle categorization model combining global feature with local feature to identify cars, pedestrians and unknown backgrounds. A new obstacle identification method, which is hybrid the global feature and local feature, is proposed for robustly recognizing an obstacle with and without occlusion. For the global analysis, we propose the modified GIST based on biologically motivated...
In this paper, a system for quality control in citrus is presented. In current citrus manufacturing industries, calliper and color are successfully used for the automatic classification of fruits using vision systems. However, fault detection in the citrus surface is carried out by means of human inspection. In this work, a computer vision system capable of detecting defects in the citrus peel and...
We propose a Bayesian image superresolution method that estimates a high-resolution background image from a sequence of occluded observations. We assume that the occlusions have spatial and temporal continuities. Such assumptions would be plausible, for example, when satellite images are occluded by clouds or when a tourist site is obstructed by people. Although the exact inference of our model is...
A computational theory concept of generating saliency maps from feature maps generated from the bottom-up approach using various filters such as a Fourier Transform was discussed. We propose a new method which generates a saliency map by using self-organized filters and not by using general filters such as Fourier transform. We extend the ICA base function estimation to the non-regular positioned...
For the purpose of object detection, Haar-Like Features (HLF) proposed by Viola [13][14] are very famous. To classify images, usually HLF and its extensions used only image intensity. However, it is well known that the gradient information of image intensity is very important for the object recognition [2][9]. So in this paper, we propose a feature which uses both intensity and gradient informations...
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