Earticle

Trip-line detection is one of the very important research topics of intelligent monitoring category. This paper will present a trip-line detection system. In our trip line detection algorithm, Gauss model is used to model background, background differencing is used to detect object. Scanning the set of points on the line, if object is cross the line, for double-direction trip-line detection system directly alerts, but for single-direction trip-line detection, the moving direction of the object must be analyzed first. If the moving direction of the object violate passing rule, system directly alerts.

In this paper, we have developed a target recognition algorithm based on a template matching technique using Synthetic Aperture Radar (SAR) images. For efficient computations, Radon transform-based azimuth estimation algorithm was used with the template matching. MSTAR data set was divided into two groups according to the depression angles, which were a train set and a test set. Template data were generated by rotating and cropping chips which were from MSTAR train set using the azimuth estimation algorithm. Then the template matching process between test data and template data was performed under various conditions. Performance variation according to contrast enhancement preprocessing which is scarce in open literature was also presented. The analysis results show that the target recognition algorithm could be useful for the automatic target recognition using SAR images.

장면전환에 따른 화질열화는 예상 비트량과 실제 부호화량의 차이가 많을 때 발생한다. 특히 장면전환이 P화면에서 발생된 경우에는 장면전환이 발생된 P화면뿐만 아니라, P화면을 참조하는 화면들의 화질에 심각한 열화가 발생한다. 본 논문에서는 장면전환이 발생했을 때 부적절한 비트율 제어의 원인을 토대로 장면전환 화면과 이후 화면들의 화질을 개선하는 방법을 제시하였다. 장면전환 화면에는 추가비트를 할당하는 기존 방법과 예상 비트를 인트라 화면의 부호화 수준으로 할당하는 새로운 방법을 적용하였다. 그리고 장면전환 이후 화면들에는 예상 비트 할당을 장면전환 발생이전 화면의 부호화 수준으로 할당하는 방법을 제안하여 화질을 개선시켰다. 실험 결과 제안하는 알고리즘이 기존 알고리즘보다 화질향상이 있었고, TM5와 비교해서는 0.5∼1.2dB의 PSNR 향상을 보였다.

The decrease of visual quality at scene change occurs when the difference between the amount of target bits and actual coding is high. Especially, scene change at the P-Picture can lead to severely degrade visual qualities at itself and the pictures referencing it. In this paper, under the occurrence of scene change, we propose a new method, based on the analysis of existing inaccurate bits allocation, to improve the visual qualities of scene-changed and following pictures. The method allocates extra bits to scene-changed Picture and changes them upto the level of the complexity of intra picture. Also, the method changes target bits of following pictures upto the complexity of picture prior to the scene change. Computer simulation shows that the proposed method has improved 0.5-1.2dB higher than TM5 method in terms of PSNR.

In this paper a fast matching method using subtemplate and search and down technique to reduce very heavy computational load of the conventional matching method, is presented The proposed method is spplied to an automatic target tracker in order to track one moving object in comparatively simple backgoriund. Experimental results show that istperformanced is not so degraded in spite of high computational reduction as that of the conventional matching method.