Object safety monitoring method and control terminal based on image processing
A security monitoring and image processing technology, applied in image data processing, image analysis, image enhancement, etc., can solve problems such as inability to effectively identify
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Embodiment 1
[0070] Please refer to figure 1 and figure 2 , Embodiment 1 of the present invention is:
[0071] An object safety monitoring method based on image processing, comprising steps:
[0072] S1. Obtain the image data to be processed, identify and intercept the plane data of the object to be detected in the image data to be processed;
[0073] In this embodiment, step S1 specifically includes steps:
[0074] S1. Obtain the image data to be processed, and use faster RCNN to identify and intercept the plane data of the object to be detected in the image data to be processed.
[0075] Among them, CNN is Convolutional Neural Networks, that is, convolutional neural network, and faster RCNN is its improved version, just refer to the existing technology.
[0076] In other embodiments, other image target detection algorithms such as YOLO (You only look once, a visual detection algorithm), RCNN, etc. may be used.
[0077] S2. Calculate and obtain the original light intensity of each p...
Embodiment 2
[0080] Please refer to figure 1 and figure 2 , the second embodiment of the present invention is:
[0081] The object safety monitoring method based on image processing, on the basis of the first embodiment above, this embodiment is applied to the climbing frame, and the climbing frame is assembled by splicing and assembling multiple climbing frame nets through the frame. Therefore, in this implementation In the example, step S2 specifically includes the following steps:
[0082] S21. Divide the planar data into a plurality of partial surface data according to the preset cutting method. When the preset cutting method is row-based cutting, execute step S22. When the preset cutting method is column-based cutting, execute step S23. When the preset cutting method is Then execute step S24 for cutting by grid;
[0083][ 1,4].
[0084] like figure 2 In the example shown, the first cutting grids are 3 in rows and columns, that is, 9 squares are cut for the first time.
[0085...
Embodiment 3
[0137] Please refer to figure 1 and figure 2 , Embodiment three of the present invention is:
[0138] The object safety monitoring method based on image processing, on the basis of the above-mentioned embodiment 2, is further limited for step S21 by grid cutting:
[0139] S211. Using image recognition technology to identify the number of spliced parts on the surface to be detected in the number of parts rows and the number of parts columns, and calculate the total number of parts;
[0140] Among them, by splicing gaps or other features between parts, CNN is used to train so that each part can be distinguished, so that the number and total number in rows and columns can be determined.
[0141] S212. Carry out Nth power on the maximum number of single cutting according to grid cutting, set the maximum value of the number of component rows and the number of component columns as the value to be cut, and judge whether the value to be cut is greater than N of the maximum number...
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