基于彩色伪随机编码结构光特征提取方法
Feature extraction method of color pseudo-random coded structured light

为增强三维重建过程中弱纹理目标的特征信息,提出一种基于彩色方格伪随机编码结构光的特征提取方法。设计一幅由五种彩色方格组成的伪随机编码结构光图案并将其投影到目标物体上。建立一种梯度算子模板对降采样图像中角点进行粗定位,然后进行局部非极大值抑制。将Harris算法推广到彩色多通道图像,对原图像粗定位区域进行角点检测,进而确定彩色图像中角点的精确位置。试验结果表明,在被测物体表面颜色和纹理结构均不丰富的条件下,提出的方法依然能够有效地保证特征提取的精度,具有较强的鲁棒性。
In order to enhance the feature information of weak texture target in three-dimensional reconstruction, a feature extraction method of structured light based on color square pseudo-random code was proposed. A pseudo-random coded structured light pattern composed of five kinds of color squares was designed and projected onto the target object. A gradient operator template was established to coarsely locate the corners of the down-sampled image. The local non-maximum was suppressed. The Harris algorithm was extended to color multi-channel images, corner detection was carried out on the coarse locating area of the original image, and then the precise position of the corner point was determined in the color image. The experiment results indicated that the proposed method could effectively guarantee the accuracy of feature extraction and had strong robustness with poor surface color and texture.