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In this paper we introduce a method for classifying terrains and for predicting friction coefficient on terrains by applying visual information. Coefficient of friction on a terrain is very important for autonomous mobile robots in driving on road and traversing over obstacle. Our algorithm is based on terrain classification for visual image. To predict friction coefficient from given image, we divide...
This paper presents a novel local threshold segmentation algorithm for digital images incorporating shape information. In image segmentation, most of local threshold algorithms are only based on intensity analysis. In many applications where an image contains objects with a similar shape, besides the intensity information, prior known shape attributes could be exploited to improve the segmentation...
Efficiently and accurately detecting pedestrian plays a very important role in many computer vision applications such as Intelligent Transportation System and Safety Driving Assistant. This paper puts forwards a two-stage pedestrian detection method based on machine vision. Firstly, the expanded Haar-like characteristic is selected and calculated using integral map and the pedestrian detection cascaded...
Adaptive local binary patterns method is proposed in this paper, on which an effective fabric defect detection algorithm is designed. ALBP method selects the frequently occurred patterns to construct the main pattern set, which avoids using the same pattern set to describe different texture structures in uniform local binary patterns method. The features of free defect image are extracted according...
The object-based attention theory has shown that perception processes only select relevant objects of the world which are then represented for action. Thus this paper proposes a novel computational method of robotic visual perception based on the object-based attention mechanism. It involves three modules: pre-attentive processing, attentional selection and perception learning. Visual scene is firstly...
The object-based attention theory has shown that perception processes only select one object of interest from the world at a time which is then represented for action. This paper therefore presents an autonomous visual perception model for robots by simulating the object-based bottom-up attention mechanism. Using this model visual perception of robots starts from attentional selection over the scene...
Image segmentation is an important and difficult task in computer vision applications. Various methods have been introduced in the past to use gray-level histogram in deciding the segmentation threshold for monochrome images. With the reducing price of color cameras, different color spaces have also been considered in color image based segmentations. In this paper, a study of the effect of color spaces...
Nowadays, more and more interest has been shown in the automatic categorization methods to organize media data as there are increasing number of videos data in people daily life. In the image processing domain, clustering method is the backbone of person specific searching and image retrieval from an image sequence or database. This paper presents a fast image clustering algorithm based on human face,...
The paper describes a gesture recognition system which can effectively recognize static single-hand gestures and be applied in complex environments. The system involves a vocabulary of 20 gestures consisting of Chinese sign language for certain letters and digits. Segmentation based on color learning and normalization based on image moment invariants are used to extract candidate hand regions. Its...
Active contour model(or'snake') is efficient in object contour extraction. It is widely applied in many fields, such as human facial feature extraction, segmenation of medical images, vedio object segmentation, 3D reconstruction, and so on. The implementation of GVF into the B Spline snake is specified, the resulting GVF B spline snake, retains the advantages of GVF snake. In this paper SOR method...
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