基于局部扫描法对倾斜指势的识别（英文）
发布时间：2018-10-25 08:20
【摘要】：为满足手指交互系统的需要,并能够达到对倾斜指势进行准确识别的要求,本文介绍了一种快速、准确对指尖检测定位并实时识别倾斜指势的方法。该方法利用YCb Cr颜色空间分割算法对肤色聚类进行粗分割,然后运用"周积比"概念对预处理区域进行细化分割,剔除除手部以外的肤色干扰区域并利用最小二乘法二项式拟合算法获取手指轮廓。采用改进的凸包络优化算法完成指尖的检测及倾斜修正。最后,进行局部扫描获得最终的指势识别。实验表明本文介绍的方法能实现简单倾斜指势0?9的识别且识别率高达95.7%,稳定性较好。
[Abstract]:In order to meet the needs of finger interaction system and to recognize the tilted finger potential accurately, this paper introduces a fast and accurate method to detect and locate the finger tip and identify the tilting finger potential in real time. In this method, YCb Cr color space segmentation algorithm is used for rough segmentation of skin color clustering, and then the concept of "circumference ratio" is used to refine and segment the preprocessed region. The skin color interference area except the hand is eliminated and the finger contour is obtained by using the least square binomial fitting algorithm. The improved convex envelope optimization algorithm is used to detect and correct the fingertips. Finally, the final finger potential recognition is obtained by local scanning. The experimental results show that the method presented in this paper can realize the recognition of simple tilting finger potential 0 / 9 and the recognition rate is as high as 95.7 and the stability is good.
【作者单位】： 上海大学新型显示技术及应用集成教育部重点实验室;上海大学微电子研究与开发中心;
【基金】：国家自然科学基金(61376028)资助项目
【分类号】：TP391.41
，
本文编号：2293150
[Abstract]:In order to meet the needs of finger interaction system and to recognize the tilted finger potential accurately, this paper introduces a fast and accurate method to detect and locate the finger tip and identify the tilting finger potential in real time. In this method, YCb Cr color space segmentation algorithm is used for rough segmentation of skin color clustering, and then the concept of "circumference ratio" is used to refine and segment the preprocessed region. The skin color interference area except the hand is eliminated and the finger contour is obtained by using the least square binomial fitting algorithm. The improved convex envelope optimization algorithm is used to detect and correct the fingertips. Finally, the final finger potential recognition is obtained by local scanning. The experimental results show that the method presented in this paper can realize the recognition of simple tilting finger potential 0 / 9 and the recognition rate is as high as 95.7 and the stability is good.
【作者单位】： 上海大学新型显示技术及应用集成教育部重点实验室;上海大学微电子研究与开发中心;
【基金】：国家自然科学基金(61376028)资助项目
【分类号】：TP391.41
，
本文编号：2293150
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