【摘要】 提出了基于手势伸展方向以及手势图像高阶NMI值的特征向量进行识别分类的算法。首先,对采集到的手势图像进行预处理与二值化,然后按手势的伸展方向进行粗分类,之后,对每幅图像提取图像的1阶和4阶NMI值,这样将一幅图像表示成一个有17维分量的特征向量。识别时用k近邻原则进行判别,识别率达到86.6%。更多还原

【Abstract】 An alphabet gesture recognition algorithm based on orientation of gesture and high-order NMI feature of the image is presented. Firstly,the images are pre-processed to get the binary image. Then the system grossly classifies the alphabet gestures according to the gesture orientationand proceeds to calculate the high-order NMI feature of the gesture image. Lastly it recognizes the unknown samples by orientation and NMIfeature. Experiments show that this method is efficacious and easy to operate.更多还原