Computer Vision-Based Rail Transit Comprehensive Fire Monitoring CCTV System and Its Realization Method

Abstract

The invention discloses a rail transit comprehensive monitoring fire circuit television system based on computer vision. The system comprises a smoke color analysis unit, a smoke main movement direction analysis unit, a video dynamic texture analysis unit and a pattern recognition unit. The smoke color analysis unit obtains the color characteristic of the smoke in the video, acquires a smoke colorspectrum and filters out the interference of a non-smoke region in the video based on the video image smoke color detection method. The smoke main movement direction analysis unit calculates the movement direction of an object moving in the video based on the frame difference method and figures out the movement direction of the smoke. The dynamic texture analysis method is adopted for the dynamictexture analysis unit of the video, and the movement interference of a steel body is eliminated. Meanwhile, a local binary pattern characteristic based on three orthogonal planes is extracted in thefluid moving object. According to the invention, the alarm response speed is accelerated, and the precious rescue time is gained. The software and hardware expenditure of an original FAS professionalis saved. The integration level of the subway comprehensive monitoring software platform is improved.

Description

technical field [0001] The invention relates to the field of urban rail transit. More precisely, the invention is applied to a subway integrated monitoring system (ISCS, Integrate Supervision and Control System), a closed-circuit television system and a fire alarm system, and belongs to the field of automation technology. Background technique [0002] With the rapid development of domestic urban rail transit, comprehensive monitoring has been widely used and developed rapidly in the subway, from the early extensive integration to the current various new technologies and methods springing up. At this stage, the subway fire alarm system uses various smoke and temperature sensors. The traditional sensor-based smoke detection system has a small monitoring range, and the sensor is prone to aging and poisoning, resulting in reduced sensitivity. Video smoke detection technology due to its short response time, The advantages of high sensitivity and large coverage area are favored by...

AI Technical Summary

Problems solved by technology

There are shortcomings such as repeated investment, difficulty in resource sharing between systems, uneven software and hardware platforms between systems, complex system structures and communication protocols, and unfavorable maintenance and management.

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