In this paper a new camera system for high speed imaging is presented which is capable of recording images with a resolution of 256x256 pixels and frame rates in excess of 1000 frames per second. It uses an image sensor with on-chip electronic shutter and has been fabricated in standard 1µm standard CMOS (Complementary Metal Oxide Semiconductor) process. The camera system contains an image memory for sequence recording. The camera system contains an image memory for sequence recording. The camera delivers a very good image quality without any external algorithm for image enhancement and provides a very fast interface between the image acquisition and image processing unit. Another among several advantages of CMOS imagers compared to their CCD (Charge Coupled Device) counterparts is the flexibility and the possibility to acquire images in a very short period. This allows an adaption of the camera to various automotive applications like occupancy detection, airbag control, precash sensing, collision avoidance, surveillance, and crash test observation. Moreover, the system architecture makes a combination of several applications possible using just a single image sensor unit
Surveillance sensors are being applied in factory automation systems, traffic control, entrapment protection, automotive safety systems and in other applications where information about the occupancy of a scene is required. In order to detect object motion several methods exploiting distinct physical phenomena, e. g. passive infrared sensors or active microwave sensors, have been realized. When comparing all of the applicable methods, the electro-optical approach outperforms with respect to the spatial resolution of the monitored area. Therefore, electro-optical sensors are able to provide additional information, e. g. to predict the direction of motion, or to localize and identify objects. However, convenient image processing systems using CCD sensors for image acquisition and DSP or µP boards for signal processing and classification are not well suited for dedicated, powerful and cost-effective optical sensor solutions. In contrast to this mainstream approach CMOS based imaging techn ologies offer novel solutions in both the design and applications of electro-optical surveillance sensors. This contribution discusses CMOS imagers operating principles and describes certain architectures and applications for passive and active surveillance sensors. The capabilities to realize on-chip motion detection and range sensing using fast shutter devices are illustrated. We conclude with a discussion of the status of CMOS surveillance sensors and suggest trends for future applications
This contribution describes a novel approach to orientation and scale-invariant detection of textured objects in images. It performs both, a segmentation of multi-object scenes and the identification of rotation angles and scale rates of textures in an image by applying comparison with reference texture features stored in a database. The main novelty of the proposed method is the transform of rotation and dilation into shifts in the feature space by employing a polar-log Gabor filter bank. Texture segmentation and identification of the rotation angles and scale rates have been carried out using symmetric phase only matched filters. The simulation results illustrated in this paper highlight the performance of the presented method in an exemplary manner
In this communication we address the problem of detection and tracking of moving objects for surveillance or occupant detection systems. The primary goal in this framework is the motion estimation of the extracted foreground. To overcome the drawbacks characteristic of classical block matching techniques, this contribution presents a new feature based hierarchical locally adaptive multigrid (HLAM) block matching motion estimation technique based on a foreground detection procedure using a robust and precise motion field estimation, close to the true motion in the scene. The simulation results highlight the superior performance of the proposed method. It yields better performance than the classical exhaustive search (ES) and the modified three-step search (MTSS) technique in terms of the peak signal-to-noise ratio (PSNR)
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