计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 210800185-6.doi: 10.11896/jsjkx.210800185
徐玥1, 周辉2
XU Yue1, ZHOU Hui21 School of Computer Science, Technology, Xi’an Jiaotong University, Xi’an 710049, China
摘要： 手势识别是人机交互中极为重要的一项技术,具有较高的理论和实践探究价值。但由于手势所处背景的复杂性、个体的差异性等原因,手势识别成为一个富有挑战性的课题。因此迫切需要设计一种高效准确的手势识别算法,用以对目标手势进行有效的检测和识别。文中提出了一种改进的手势分割和手势特征提取方法,利用SVM分类器构建手势模型,对手势进行分类识别。在YCrCb颜色空间的基础上,融合OTSU阈值处理法选取阈值分割手势,提高分割的准确度;在边缘检测的基础上,使用椭圆傅里叶描述子拟合边缘,提取手势特征。实验结果表明,运用上述算法所建立的系统能够十分高效地提取手势特征信息,且在简单背景下对13种常见手势的平均识别准确率达到89.96%,能够基本满足对手势识别的精确度和稳定性的要求。
中图分类号:
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