基于视差和条纹调制度分析的多物体场景分割

噪声是影响图像分割的重要因素，文中提出了一种能够在含噪声的真实场景中准确提取出多个物体区域的分割方案。利用基于正弦条纹投影的双目结构光系统，得到包含目标物体的相位图和视差图。将视差图映射到U-视差图中，利用物体和噪声区域在该视差空间的不同形态特征，采用闭合区域检测算法初步得到各个物体的分割区域，并结合条纹调制度阈值分析法进一步去除阴影区域的噪声，最终得到精确的分割结果。客观评价的数据分析表明，文中提出的分割算法，不仅对噪声的鲁棒性较好，还可以有效地将物体与水平支撑面分割开，在不同场景下具有计算复杂度低，抗干扰能力强的优势，分割准确率均在90%以上，最高可达到99.2%，平均运行时间为27 ms。

Segmentation in multi-objects scene based on disparity and fringe modulation analysis

Noise is an important problem that affects image segmentation. A novel scheme was proposed that could accurately extract multiple objects in a noisy real-world scene. The phase map and disparity map were obtained by using the binocular structured light system based on sinusoidal fringe projection. Firstly, a disparity map was transformed into the corresponding U-disparity map. Then, according to the different projection characteristics of object and noise regions in the disparity map, the preliminary segmentation regions were obtained by using the closed region detection algorithm. In addition, the fringe modulation analysis method was used to remove the noise in the shadow region, and the accurate segmentation results were finally obtained. Experimental results and objective evaluation data indicate that the proposed segmentation algorithm in this paper is not only robust to noise but also can effectively separate the object from the horizontal support surface. It has the advantages of low computational complexity and strong anti-interference ability in different scenarios. The average segmentation accuracy is above 90%, and the best accuracy can achieve 99.2%. The average running time is almost 27 ms.