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Obstacle avoidance is an important and challenging task for the autonomous flight of unmanned aerial vehicles. Obstacle regions extraction from image sequences is a critical prerequisite in obstacle avoidance. We propose an obstacle regions extraction method based on space–time tensor descriptor. In our method, first, the space–time tensor descriptor is defined and a criterion function based on the descriptor of extracting space–time interest points (STIPs) is designed. Then a self-adaptive clustering of STIPs approach is presented to locate the possible obstacle regions. Finally, an improved level set algorithm is applied with the result of clustering to extract the obstacle regions. We demonstrate the experiments of obstacle regions extraction by our method on image sequences. Sequences are captured in indoor simulative obstacle avoidance environments and outdoor real flight obstacle avoidance environments. Experimental results validate that our method can effectively complete extraction and segmentation of obstacle region with captured images. Compared with the state-of-the-art methods, our method performs well to extract the contours of obstacle regions on the whole and significantly improves segmentation speed.

The paper presents a universal development environment of application domain-oriented knowledge discovery system - KDIST. Based on graphic modeling and intelligent guidance techniques, KDIST is user-friendly enough for generic people to develop a knowledge discovery system with expertise as little as possible. Not only discovering knowledge from data with high performance, but can the developed knowledge discovery system add discovered knowledge to a relative knowledge base and then refine knowledge on the premise of keeping consistence of the knowledge base.

Under identical irradiation conditios, higher concentrations of F2+, F2-, and F2 centers in lightly doped LiF: OH- than in pure LiF are found, but thermal stability of F2+ center in these two samples is almost the same. Products of OH- decomposition play an important roles in the formation and thermal decay processes of these F-aggregate centers.