Advanced Materials Research Vols. 998-999

Abstract: we studies the grenade fragment to view damage effect of aiming an armored vehicle parts (fragment size, shape, fragment velocity) with the finite element method,The damage processs of grenade fragments of armored vehicle concept aiming component is simulated by the AUTODYN software. Through the analysis of the results of numerical simulation,weobtained parameters values at the damage assessment components (attenuation penetration depth, diameter and velocity degree) and grenade fragment to the gunner aimed at the damage rule, mirrorand lay the foundation for the fragment of the armored equipment parts damage assessment.

Abstract: In this paper, a space-based optical surveillance system was designed based on the research of geostationary (GEO) objects. Firstly, a strategy to observe the pinch point region was researched. Then, the orbit type of surveillance system and sensor pointing were analyzed, a equation set was deduced to guide the system design. The simulation result demonstrates that the revisit time of the surveillance system designed in this paper is less than one day, and the average coverage time is about 900s per day. The system can observe most of the GEO belt objects.

Abstract: In order to automatic organization data according to customers’ requirement, and improve the data reusability, an idea of data meta-component is proposed, the definition of data meta-component is present, the model of data meta-component is established. A theme-oriented data automatic organization method is proposed; on the basis of data mete-component, the theme domain data automatic organization is realized by means of nature language processing, semantic query, association analysis, share distribution, and other technologies; experimental results show that this method is feasible and effective.

Abstract: A novel two-dimensional (2D) direction-of-arrival (DOA) estimation algorithm utilizing a sparse signal representation of higher-order power of covariance matrix is proposed. Through applying the higher-order power of covariance matrix to construct a new sparse decomposition vector, this algorithm avoids the estimation of incident signal number and eigenvalue decomposition. And the hierarchical granularity-dictionary is studied, which forms the over-complete dictionary adaptively in the light of source signals’ distribution. Compared with MUSIC and L1-SVD, this algorithm not only provides a better 2D DOA performance but also possesses the capability of coherent signals estimation. Theoretical analysis and simulation results demonstrate the validity and robust of the proposed algorithm.

Abstract: In the ordinary video monitoring system, the whole small scene is usually observed by a stationary camera or a few stationary cameras, but the system can’t zoom and focus on the target of interest rapidly, and also can’t get the high resolution image of the target of interest in a far distance. Therefore based on the research of the dual-camera cooperation and a RSOM clustering tree and CSHG algorithm, a cooperative dual-camera system is designed to track and recognize a face quickly in a large-scale and far-distance scene in this paper, which is made up of a Stationary Wide Field of View (SWFV) camera and a Pan-Tilt-Zoom (PTZ) camera. In the meanwhile, the algorithm can ensure the real-time requirement.

Abstract: Optimal path selection is a fundamental problem in tourism, the influence factors of which only including the rout length, but also including weather, transportation and the scenery of attractions and other relevant factors. Therefore, route selection only based on the route length cannot capture the actual requirement. The paper studies the multi-weights (such as weather, route length, attractions scenery and etc.) in route selection, and then proposed an improved ant colony algorithm based on multi-weights (ACA-MW), which uses the multi-weights ant and the genetic variation to search optimal path. Simulated experiment of the ACA-MW shows high performance, the improved algorithm is effective. In tourism, ACA-MW can do well in optimal path selection problem.

Abstract: In video indexing and retrieval systems, textual information is high-level semantic content to describe images or video frames, which is also one of the most interesting objects of study. A great progress has been made in text detection in recent decades, but it is still a great challenge due to the complex background, various fonts and different languages, etc. In this paper, we propose a edge-based approach to detect artificial text. First, the image edge map and difference range map are calculated. Then the map is binarized by local threshold method. Finally the textual information is located through the regional projection analysis. Experience results show our method’s precision rate is 91.1% and recall rate 93.2%, which outperforms the previous work.

Abstract: This paper introduces a novel image encryption scheme based on chaotic maps and toggle cellular automata (TCA). In confusion stage, the proposed scheme utilizes logistic map to construct a nonlinear sequence for scrambling the plain-image. Then in diffusion stage, TCA is constructed by setting up the inversion rule and the image which has been processed by chaotic sequence is encryption again by using the TCA iteration method. Theoretical analysis and experimental results demonstrate the proposed algorithm achieves a high security level and processes good performance against common attacks like differential attack and statistical attack.

Abstract: Boundary detection is a critical, well-studied computer vision problem. Clearly it would be nice to have algorithms which know where one object stops and another starts. Traditional approaches look for intensity discontinuities in an image, however we believe that detecting boundary from a single image is fundamentally difficult, whereas machine learning techniques have a promising prospect on boundary detection. A novel learning model is proposed in this paper. Random decision forest classifier trained by human segmentation images will applied to determine the mapping from image patches to boundary probabilities. The results on BSDS500 dataset show that our model ties the performance of other competing approaches, but being magnitude faster than others.

Abstract: Realistic image synthesis technology is an important part in computer graphics. Monte Carlo based light simulation methods, such as Monte Carlo path tracing, can deal with complex lighting computations for complex scenes, in the field of realistic image synthesis. Unfortunately, if the samples taken for each pixel are not enough, the generated images have a lot of random noise. Adaptive sampling is attractive to reduce image noise. This paper proposes a new GH-distance based adaptive sampling algorithm. Experimental results show that the method can perform better than other similar ones.