Monitoring image processing method and device, monitoring system and storage medium

Abstract

The embodiment of the invention provides a monitoring image processing method and device, a monitoring system and a storage medium, relates to the technical field of image processing, and the method, the device and the system can reduce a monitoring blind area in a long, narrow and deep monitoring scene. The monitoring image processing method comprises the steps that a first image sent by a camera is received, the aspect ratio of the first image is a / b, the first image is subjected to 90-degree rotation operation to form a rotated second image, the aspect ratio of the second image is b / a, a display picture is generated, the display picture comprises the second image, the aspect ratio of the second image in the display picture is b / a. The technical scheme is mainly used for an image monitoring process.

Description

technical field [0001] The present application relates to the technical field of image processing, and in particular to a monitoring image processing method, device, monitoring system and storage medium. Background technique [0002] The aspect ratio of images captured by traditional surveillance cameras is usually 16:9 or 4:3. In narrow, long and deep surveillance scenarios, such as figure 1 as shown, figure 1 It is a schematic diagram of a monitoring image in an aisle scene in the prior art. The effective monitoring area corresponding to the monitoring image is relatively small. There are monitoring blind spots in the location. For example, when detecting people left in the car, it is easy to cause the problem of unrecognizable or inaccurate recognition. Although there is currently a corridor mode set by the network camera to collect images with an aspect ratio of 9:16 to improve the effective monitoring area in narrow, long and deep scenes, but for scenes without a netw...

AI Technical Summary

Problems solved by technology

[0002] The aspect ratio of images captured by traditional surveillance cameras is usually 16:9 or 4:3. In narrow, long and deep surveillance scenarios, such as figure 1 as shown, figure 1 It is a schematic diagram of a monitoring image in an aisle scene in the prior art. The effective monitoring area corresponding to the monitoring image is relatively small. There is a monitoring blind spot in the location. For example, when detecting the occupants in the car, it is easy to cause the problem of unrecognizable or inaccurate recognition

Although there is currently a corridor mode set by the network camera to collect images with an aspect ratio of 9:16 to improve the effective monitoring area in narrow, long and deep scenes, but for scenes without a network such as inside a bus, it is still necessary to use traditional cameras. Realize monitoring, so when using camera monitoring, there is still the problem of large monitoring blind spots in narrow, long and deep monitoring scenarios

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