关键词: 凸性, 凸分组, 最优化判定, 目标检测

Abstract: Combining with the convex characteristics of each object in the world, this paper proposes a single object detection method in the static image based on the best optimization convex grouping. The basic principle of the best optimization convex grouping is discussed systematically. Then the implementation process is designed in detail. The whole process steps include the parameter setting of the Canny edge detector, linear fitting based on the edge points, how to structure the convex polygons and the best optimization decision method for convex polygon. The experimental results are shown that this method can detect the single object from the static image at any environment, and it has higher detection rate and detection accuracy. It is not affected by the quantity and quality of sample in the machine learning, so it has a better general application for any single object and any environment.

Key words: convex attribute, convex grouping, best optimization decision, object detection