Multi-point detection and calculation method for touch screen

Abstract

The invention discloses a multi-point detection and calculation method for a touch screen. The method comprises the following steps: 1) starting a camera and collecting a touch image; 2) carrying out binary processing on the touch image, thus getting pixel value of the touch image; 3) comparing the collected pixel value with the preset pixel value, and storing corresponding pixel coordinates of the touch image if the collected pixel value is larger than the preset value; and 4) using a back-end processing module to read out the stored pixel coordinates, adopting the gravity center algorithm which is near to a touch point pixel family to classify each pixel coordinate and re-calculate the gravity center of the touch point pixel family, and finally identifying one or more touch points. By adopting the method, two touch points which are near to each other and even communicated at boundaries can be rapidly and accurately identified, and the reliability is high.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a multi-point detection and calculation method of a touch screen based on camera positioning. Background technique [0002] In recent years, large-screen touch technology has made great progress. Infrared LED scanning touch screens, ultrasonic touch screens, touch screens positioned behind the camera, and touch screens with two cameras installed at the corners of the touch screen have appeared. Among them, positioning the touch screen behind the camera can be convenient. It can flexibly implement multi-touch, and it is easier to monitor and track more than two touch points, so it has been widely used in the field of multi-touch. [0003] Position the touch screen behind the camera, generally binarize the images collected by the camera, that is, set a predetermined value, compare the brightness information of the pixels collected by the camera with the predetermined value, and the p...

AI Technical Summary

Problems solved by technology

This is a very intuitive method to distinguish different touch points. Since the image collected by the camera is binarized, the touch point pixels obtained after processing and the coordinates of the effective pixels contained in the same touch point are not strictly continuous. , there will be a distance of several pixels between individual effective pixel coordinates, but they belong to the same touch point. In this way, using this intuitive method to determine the touch point based on the distance between pixel coordinates, in order to improve the accuracy of the determination, often Set the judgment distance boundary to several pixels. If the distance between two effective pixels is less than the set several pixels, it is considered as the same touch point, otherwise, it is considered as a different touch point. If the distance between the two fingers is Relatively large, this method of determination is acceptable, but if the distance between the two fingers is relatively small, or even if the two fingers are close together, this method of determination will produce wrong coordinates of the touch point, because the two fingers are close to each other When this judgment sets the distance between pixels, this algorithm considers the touch point of two fingers as one touch point, resulting in a judgment error, and unreliable coordinates are generated during multi-point operation, resulting in gesture operation and finger close-up. Errors such as drawing lines

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