Elevator door state detecting method and system based on image column diagram

Abstract

The invention discloses an elevator door state detecting method based on an image column diagram. The method comprises the following steps that 1, video image information in a car platform sill is collected; 2, analysis is carried out according to the collected video image information, whether an elevator door of the elevator car platform sill monitored currently is in an opening state or not is judged, and the result is conveyed to a data analyzing unit; and 3, according to a detecting area transmitted by a video collecting module, a door state detecting unit registers a background template under the door complete closing state in an H channel of an HSV space, constantly calculates the difference between a current frame column diagram and a background column diagram later, and judges theopening and closing state of the door.

Description

technical field [0001] The invention belongs to the technical field of elevator safety, and in particular relates to an elevator door state detection method and system based on an image histogram. Background technique [0002] At present, the elevator has become the standard equipment in many buildings in the city, and it is an important means of transportation for people in modern life. Due to its frequent use and its own airtight characteristics, the elevator environment has a strong demand for image monitoring. The traditional elevator monitoring only has the basic video recording function, and cannot intelligently judge the current state of the elevator door. When the elevator fails suddenly, the community management personnel can only query the monitoring images laggingly, and the crisis handling mechanism responds slowly and has certain hysteresis. [0003] Chinese invention patent application CN106204659A discloses an elevator door opening and closing detection meth...

AI Technical Summary

Problems solved by technology

There are following deficiencies in this technical solution: (1) It is necessary to extract corner points from the four sub-regions of the region of interest at the same time, and perform optical flow tracking respectively, and count the direction of motion

The whole process is slightly cumbersome and the amount of calculation is large

(2) The local image feature detection method using optical flow tracking corner points is greatly affected by changes in external lighting. Once the lighting of the elevator car itself changes greatly, or the external lighting interference caused by opening and closing doors, the tracking algorithm will fail.

There are the following deficiencies in the technology of this solution: (1) This solution can only use depth cameras as monitoring equipment, and the cost of depth cameras is relatively high

Images