传统的机器视觉采用二维RGB图像,难以满足三维视觉检测的要求,深度图像能直接反映物体表面的三维特征,正逐渐受到重视。该文提出的方案将RGB和深度信息相结合,分割出物体所在区域,并利用梯度方向直方图(HOG,histograms of oriented gradients)分别提取RGB图像和深度图像特征信息。在分类算法上,该文采用k最邻近节点算法(k-NN)对特征进行筛选,识别出目标物体。试验结果表明,综合利用深度信息和RGB信息,识别准确率很高,此方案能够对物体和手势进行很好识别。
The traditional machine V1Slon with RGB image doesn't meet the requirements of the 3D visual inspection. The Range 1mage can reflect the 3D characteristics of the object surface directly, and is attracting much more attentions gradually. How to use the RGB and depth information for object recognition is the core issue, which would be studied in this paper. Firstly, based on the kinect color and depth information, the object recognition system was put forward in this paper. The kinect sensor was used to acquire the color and depth information of the target object and its background in recognition system. The information can be used to segment the object from the background. Then HOG feature descriptor was used to extract the target sample's characteristics and establish the characteristic model. 1n the actual process of object recognition, the most similar templates category with k-NN algorithm was selected to achieve the goal of classification and recognition.