Image recognition stitching method and system in big data monitoring system
A monitoring system and image recognition technology, which is applied in image analysis, image enhancement, graphics and image conversion, etc., can solve problems such as large amount of calculation, low matching accuracy, and high cost
Active Publication Date: 2022-04-26
鹏祥智慧保安有限公司
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Problems solved by technology
This method, on the one hand, needs to pass through multiple cameras, which are expensive and costly; on the other hand, the matching method based on the depth value is computationally intensive and the matching accuracy is low
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Embodiment
[0058] An embodiment of the present invention provides an image recognition and stitching method in a big data monitoring system, which is used to identify and stitch two images that need stitching, such as figure 1 As shown, the image recognition stitching method in the big data monitoring system includes:
[0059] S101: Obtain two images that need to be spliced, and the two images include a first image and a second image.
[0060] Wherein, the image may be an image captured by a CCD camera. Specifically, the monitoring server in the big data monitoring system obtains the two spliced images from the big data, or the two images that need to be spliced are captured by the CCD camera and sent to the monitoring server, and the monitoring server executes S101~S109 step.
[0061] S102: Extract feature points in the first image and the second image respectively.
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The invention discloses a precision medical image analysis method and a robotic surgery system, which can obtain multiple images of lesion parts; partition each image, and obtain multiple regional images corresponding to each image; The images are constructed into area chains in the order of shooting time; multiple area chains are input into the linkage analysis model at the same time; the fully adaptive mapping network obtains the disease characteristics of the lesion according to the output value of the linkage analysis nodes of the linkage analysis network in the output layer, and the The disease characteristics include the predicted disease type and severity for the lesion. Because the linkage analysis nodes of the linkage analysis network on the same layer can influence and adjust each other, the linkage analysis nodes corresponding to each other on the upper and lower layers can also influence and adjust each other. Subtle to cell-to-cell effects are analyzed.
Description
technical field [0001] The invention relates to the field of monitoring, in particular to an image recognition splicing method and system in a big data monitoring system. Background technique [0002] Surveillance systems are widely used in banks, shopping malls, company office buildings, buses, subways, urban roads, expressways, and schools to monitor areas in these places to improve the safety of these areas. In the field of panoramic monitoring, image recognition and splicing are necessary means to obtain panoramic images. [0003] In the prior art, panoramic images mainly come from images of different angles taken by multiple cameras, and these images are matched based on depth values to obtain matched image point pairs, and then image stitching is realized. This method, on the one hand, needs to pass through multiple cameras, and the cameras are expensive and expensive; on the other hand, the matching method based on the depth value is computationally intensive and t...
Claims
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IPC IPC(8): G06T3/40G06T7/33
CPCG06T3/4038G06T7/33G06T2207/10004
Inventor 姜培生卢海鹏其他发明人请求不公开姓名
Owner 鹏祥智慧保安有限公司