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Method and device for identifying video monitoring scenes

A technology of video monitoring and discrimination method, which is applied in the direction of digital video signal modification, closed-circuit television system, electrical components, etc. It can solve the problems of affecting video monitoring effect, poor quality of video monitoring image transmission, and limited upstream bandwidth, etc., and achieves improvement. The Effect of Video Surveillance Image Quality

Inactive Publication Date: 2014-02-05
CHINA MOBILE COMM GRP CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the limited uplink bandwidth of 3G wireless networks such as TD-SCDMA, the transmission quality of video surveillance images is poor, which greatly affects the effect of video surveillance

Method used

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  • Method and device for identifying video monitoring scenes
  • Method and device for identifying video monitoring scenes
  • Method and device for identifying video monitoring scenes

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0035] Embodiment 1, the discrimination of motion / stationary scene:

[0036] Such as Figure 4 As shown, it is a processing flow chart for judging whether a video monitoring scene is a motion / stationary scene proposed by an embodiment of the present invention, wherein motion detection can be used to judge whether a video monitoring scene is a motion scene or a static scene, and the current frame of the video to be monitored Subtract the image from the previous frame to obtain the residual frame. If there is no motion at the corresponding positions of the two frames before and after, the brightness value of the pixel at the corresponding position of the obtained residual frame (referred to as the brightness value for short) is zero; Pixel Luminance Value Non-zero luminance value. The luminance value of each pixel in the residual frame is counted. If the ratio of the number of pixels with non-zero luminance value to the number of all pixels contained in the residual frame is g...

Embodiment 2

[0043] Embodiment 2, Discrimination of Daytime / Nighttime Scenes:

[0044] Such as Figure 6 As shown, it is a processing flow chart for judging that a video surveillance scene is a daytime / nighttime scene proposed by the embodiment of the present invention. The embodiment of the present invention is based on the brightness value in the image frame representing the brightness of the image, and by counting the brightness of all pixels in a frame of image If the average brightness value obtained by statistics is greater than a certain threshold value, it can be judged that the monitoring scene where the front-end video surveillance device is located is a daytime scene; if the average brightness value obtained by statistics is lower than this threshold value, it can be judged that the front-end video surveillance The monitoring scene where the device is located is a night scene. The specific implementation process is as follows:

[0045] Step 60, obtaining the current video imag...

Embodiment 3

[0050] Embodiment 3, indoor / outdoor scene discrimination:

[0051] Such as Figure 8 As shown, it is a processing flow chart for distinguishing a video monitoring scene as an indoor / outdoor scene proposed by the embodiment of the present invention. The embodiment of the present invention distinguishes between an indoor monitoring scene or an outdoor monitoring scene and mainly focuses on whether the video image frame has uniform illumination. The monitored video image frames generally have uneven illumination, such as lighting and other effects. Divide a monitored frame of image into blocks of 16x16 pixels (of course, it can also be divided into blocks of other sizes, such as 8×8, 4×4, etc.), and calculate the brightness of each divided pixel block Mean value Y, obtain the maximum brightness mean value Y of the pixel block in a frame of image max and minimum brightness mean Y min , as obtained by Y max and Y min If the following formula is satisfied, it is judged that the...

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Abstract

The invention discloses a method and device for identifying video monitoring scenes. The method for identifying the video monitoring scenes comprises the steps of (1) obtaining a front video image frame and a current video image frame obtained through monitoring of a front-end video monitoring device; (2) carrying out subtraction between the front video image frame and the obtained current video image frame to obtain an image residual frame; (3) determining brightness values of pixels of the obtained image residual frame; (4) determining the value of the ratio of the number of the pixels with the nonzero brightness values to the number of all the pixels of the image residual frame according to the determined brightness value of each pixel; (5) determining that the current monitoring scene where the front-end video monitoring device is located is a moving scene when the determined value of the ratio is larger than a set ratio threshold value; (6) determining that the current monitoring scene where the front-end video monitoring device is located is a static scene when the determined value of the ratio is smaller than or equal to the set ratio threshold value. The method and device for identifying the video monitoring scenes can achieve identification of the different monitoring scenes.

Description

technical field [0001] The present invention relates to the technical field of video surveillance, in particular to a video surveillance scene discrimination method and device. Background technique [0002] At present, with the maturity of the security industry and the large-scale construction of safe cities and safe campuses, people pay more and more attention to real-time remote monitoring, and video surveillance has been more and more widely used. Video surveillance has also evolved from wired to wireless to meet the ever-increasing requirements for mobility and convenience. However, due to the limited uplink bandwidth of 3G wireless networks such as TD-SCDMA, the transmission quality of video surveillance images is poor, which greatly affects the effect of video surveillance. [0003] While increasing the transmission bandwidth of the wireless network, it is also necessary to optimize the video encoding method at the source end to improve the quality of video image tran...

Claims

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Application Information

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IPC IPC(8): H04N7/18H04N19/142H04N19/517H04N19/527H04N19/176H04N19/94H04N19/60
Inventor 杨黎波柴鑫刚张俭
Owner CHINA MOBILE COMM GRP CO LTD
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