A fingertip detection method based on least square curve fitting

Abstract

The invention discloses a fingertip detection method based on least square curve fitting. The method comprises the following steps: firstly, carrying out skin color model segmentation in an RGB colorspace to obtain a hand region, then obtaining a hand peripheral contour by adopting a contour extraction method, fitting a parabola on a section of curve in an adjacent range at each point of the contour by using a least square method, and accumulating distances from points at a certain interval distance to tangent lines where the points are located as the curvature; and setting a threshold value,judging the point of which the curvature is greater than the threshold value as a similar fingertip point, and finally limiting the finger width to eliminate non-fingertip points. According to the method, the quadratic polynomial curve is used for fitting the upper end part of the finger, the fingertip point is detected by setting the threshold value and the finger width limit, the fingertip positioning accuracy is high, the detection result is not influenced by the change of the distance between the hand and the camera, and the method still has a good detection effect and relatively high robustness when the form of the finger is changed by a certain amplitude.

Description

technical field [0001] The invention relates to the field of machine vision, in particular to a fingertip detection method based on least squares curve fitting. Background technique [0002] The continuous development of computer application technology has made human-computer interaction methods more diverse. Traditional human-computer interaction methods such as keyboards, mice, and touch screens require manual manipulation of hardware devices, which are stable and reliable, but inflexible. The new human-computer interaction method is more convenient and intelligent by using machine vision, pattern recognition and other related technologies to understand human behavior and instructions contained in voice, and then execute corresponding operations. Fingertip detection based on machine vision solves the problem of obtaining fingertip information in human-computer interaction. [0003] For fingertip detection, it is necessary to extract the hand area according to the hand fea...

AI Technical Summary

Problems solved by technology

However, in order to achieve the ideal fingertip detection effect, most of the fingertip detection algorithms in the prior art are limited to static gestures. When the distance between the hand and the camera changes, or the bending shape of the finger changes, it cannot accurately and effectively locate the fingertip. tip

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