融合修正OTSU 和中值滤波的水上航行器障碍物视觉分割

为进一步提高水上航行器视觉避障时图像分割的精确性，提出融合修正OTSU 和中值滤波的水上航行器 障碍物图像分割算法。利用修正系数将原始图像从RGB 模型转换为Y、Cb、Cr 色度值修正的模型，进行修正OTSU 的阈值分割，对分割后的二值图像实行自适应中值滤波降噪处理，并对3 种水上障碍物识别算法进行测试。结果表 明：与加权Otsu 算法和改进阈值分割算法对比，该算法可以将检测目标区域占比稳定在80%以上，并将干扰噪声区 域占比降低至28.5%，说明算法有效、可行。

Visual Segmentation Incorporating Modified OTUS and Median Filtering for Obstacles of a Watercraft

In order to further improve the accuracy of image segmentation for visual obstacle avoidance of watercraft, an image segmentation algorithm for watercraft obstacle based on fusion of modified OTSU and median filter (VSAIMOAMF) is proposed. The original image is transformed from RGB model to Y, Cb, Cr chroma value modified model by using correction coefficient. The threshold segmentation of modified OTSU is carried out. The segmented binary image is processed by adaptive median filtering and noise reduction. Three water obstacle recognition algorithms are tested. The results show that, compared with the weighted Otsu algorithm and the improved threshold segmentation algorithm, the algorithm can stabilize the proportion of the detection target area to more than 80%, and reduce the proportion of the interference noise area to 28.5%, which shows that the algorithm is effective and feasible.