Image detection method, device and equipment and computer storage medium
A technology for image detection and to-be-detected images, which is used in image communication, parts of color TVs, parts of TV systems, etc., to achieve the effect of improving image recognition performance
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Embodiment 1
[0042] figure 1 The flow chart of the method provided by Embodiment 1 of the present invention, such as figure 1 As shown in , the method may include the following steps:
[0043] In 101, the image data of the image to be detected in the grayscale color space is acquired.
[0044] The backlight detection in the present invention is based on the image to be detected, and the way to acquire the image to be detected is different for different scenes. This part will be specifically covered in the subsequent scenario examples.
[0045] The so-called color space refers to the use of spatial coordinates to describe the color range. The commonly used color spaces mainly include RGB (red, green, blue) color space, CMYL (cyan, magenta, yellow, black) color space, LAB (lightness, A channel) , B channel) color space, etc. The color space used in the embodiment of the present invention is a grayscale color space. After the image to be detected is obtained, the color space used by the ...
Embodiment 2
[0060] figure 2 The flow chart of the method provided by Embodiment 2 of the present invention, such as figure 2 As shown in , the method may include the following steps:
[0061] In 201, the image data of the image to be detected in the grayscale color space is acquired.
[0062] In 202, execute figure 1 102 and 103 in the flow shown.
[0063] use figure 1 In the manner described above, determine the luminance cumulative histogram of the image data to be detected under the grayscale color space, and determine the slope of the luminance cumulative histogram variation of each luminance interval relative to the luminance value. For details, refer to relevant records in Embodiment 1, and details are not repeated here.
[0064] In 203, determine the grayscale distribution mean and variance of the image data to be detected under the grayscale color space.
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