This paper presents a learning-based visual inspection method that addresses the need for an improved adaptability of a visual inspection system for parts verification in panorama sunroof assembly lines. It is essential to ensure that the many parts required (bolts and nuts, etc.) are properly installed in the PLC sunroof manufacturing process. Instead of human inspectors, a visual inspection system can automatically perform parts verification tasks to assure that parts are properly installed while rejecting any that are improperly assembled. The proposed visual inspection method is able to adapt to changing inspection tasks and environmental conditions through an efficient learning process. The proposed system consists of two major modules: learning mode and test mode. The SVM (Support Vector Machine) learning algorithm is employed to implement part learning and verification. The proposed method is very robust for changing environmental conditions, and various experimental results show the effectiveness of the proposed method.

An effective dual-mode camera system(a passive wide-angle camera and a pan-tilt-zoom camera) is proposed in order to improve the performance of visual surveillance. The fixed wide-angle camera is used to monitor large open areas, but the moving objects on the images are too small to view in detail. And, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a specific moving target. However, its FOV (Field of View) is limited when zooming in on a specific target. Therefore, the cooperation of wide-angle and PTZ cameras is complementary. In this paper, we propose an automatic initial set-up algorithm and coordinate transform method from the wide-angle camera coordinate to the PTZ one, which are necessary to achieve the cooperation. The automatic initial set-up algorithm is able to synchronize the views of two cameras. When a moving object appears on the image plane of a wide-angle camera after the initial set-up positioning, the obtained values of the wide-angle camera should be transformed to the PTZ values based on the coordinate transform method. We also develope the PTZ control method. Various in-door and out-door experiments show that the proposed dual-camera system is feasible for the effective visual surveillance.Keywords: dual-camera system, visual surveillance system, moving object tracking

In this paper, we propose a tracking and recognition of pedestrian/vehicle for intelligent multi-visual surveillance system. The intelligent multi-visual surveillance system consists of several fixed cameras and one calibrated PTZ camera, which automatically tracks and recognizes the detected moving objects. The fixed wide-angle cameras are used to monitor large open areas, but the moving objects on the images are too small to view in detail. But, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a target. The proposed system is able to determine whether the detected moving objects are pedestrian/vehicle or not using the SVM. In order to reduce the tracking error, an improved camera calibration algorithm between the fixed cameras and the PTZ camera is proposed. Various experimental results show the effectiveness of the proposed system. 키워드 : 화상감시시스템, 물체추적, 물체인식