To effectively detect the camouflaged target in the complex background, the target detection method based on 3D convexity is proposed in this article. This method uses a new operator which can fully utilize the representative image gray level represented by the convexity structure of the target, set up appropriate threshold to eliminate the influence of the background noise by the median filtering through the gray face of the target image, and realize the effective detection and identification of the convexity target. The experiment result shows that this method could successively detect the camouflaged targets in the complex background, better than classic edge detection method. As a new camouflaged target detection and evaluation technology, this method can provide necessary factors for the design and implementation of the camouflage technology, and promote the development of the camouflage technology. Keywords: Camouflage, Detection, Convexity 1. Introduction The optical camouflage technology usually utilizes various measures to hide, cover, or fade the optical characteristics such as outline and texture of the targets, and make them to be integrated in the background. The usual evaluation method of the effect depends on the manual work to obtain the discovery probability, and this method has certain subjectivity, without strong reliability, such as the Johnson criterion early used by the US army. With the development of the digital image processing technology, some foreign countries begin to use the image characteristics to design, detect, and identify the camouflaged target, and at the same time, the objective analysis and evaluation technology research about the camouflage effect have also been developed. For example, David E. Schmieder et al utilized the contrast ratio of the video image to analyze the relationship between the distinguishability and the discovery probability under different mottled backgrounds, and compared with the result of manual work (David E, Schmieder, 1983, P. 622-630). E. J. Kelman et al studied the body color comparison and vision characteristic of inkfish image, and extracted edges by analyzing the main component quantity of the characteristic, and set them into the chessboard to detect and identify them, and analyzed the effect of the transformed camouflage (E.J. Kelman, 2007Kelman, , P. 1369Kelman, -1375. The National Defense Research Center of Denmark developed the camouflage effect simulation evaluation software (CAMEVA) in 1998, and there are several conversion now, and this software extracts the characteristics of the input image, and analyze the statistical result, and in the detector model and the atmosphere transmission model, the detection distance is obtained by the trained minimum scene distinguishability parameter to evaluate the camouflage effect and the detectability of target (Christian M. Birkermark, 1999, P. 229-238), and these researches are mainly centralized in the edge and texture characteristics of the target and background. Li Junwei et al demon...

Through the analysis of common moving target detecting algorithms, this paper proposes a moving target detecting algorithm based on S usan edge detection and frame difference. It detects the edge information of current frame image by Susan operator, then taking a differential operation between the current frame and the next frame image to get the outline of moving target. Finally, it extracts the target by using an and operation with two parts of information. The experimental results show that this algorithm is simple and effective, making up for the deficiency of a single frame difference method.

In order to assess threat of reentry-course ballistic missile comprehensively and rationally,a concept of defense object is put forward,which is integration of conservation-shot resource and theater critical area;then index system of threat assessment of reentry-course ballistic missile and frame of model is constructed;on this basis,quantized method of index system is gived and threat assessment model of multiple defense object and multiple ballistic missile is established;frame and algorithm flow of grey relationship analysis based on entropy is proposed. Practically applications indicate that the model is valid and the algorithm is feasible.

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