摘要
船舶图像特征分割和提取算法是图像检测领域中的基础工作。由于船舶航运环境和船舶自身结构组成相对复杂,船舶图像的全自动分割方法在图像检测过程中经常出现边缘模糊、准确性低等问题。因此提出基于图像检测的船舶特征分割与提取优化算法,结合免疫算法获取更多图像特征信息,达到快速、准确的对船舶图像特征进行提取和分割的目的。为验证算法的准确性进行仿真实验,结合船舶区域图像对图像边界特征进行提取和分割,并与传统方法进行比较。实验结果证明基于图像检测的船舶特征分割与提取优化算法可以有效达到特征融合、全局最优、算法效率高等优良特性,使图像具有更强的实用性。
Ship image feature segmentation and extraction algorithm is the basic work in the field of image detection.Due to the complexity of shipping environment and ship's structure,the automatic segmentation of ship images often has the problems of fuzzy edges,low accuracy and so on in the process of image detection.Therefore,a ship feature segmentation and extraction optimization algorithm based on image detection is proposed,which combines with immune algorithm to obtain more image feature information,so as to achieve the purpose of fast and accurate ship image feature extraction and segmentation.In order to verify the accuracy of the algorithm,simulation experiments were carried out to extract and segment the image boundary features,and compared with the traditional methods.The experimental results show that the ship feature segmentation and extraction optimization algorithm based on image detection can effectively achieve the characteristics of feature fusion,global optimization,high algorithm efficiency and so on,which makes the image more practical.
出处
《舰船科学技术》
北大核心
2018年第4X期142-144,共3页
Ship Science and Technology
基金
国家自然科学基金资助项目(61503260)
关键词
免疫遗传算法
图像检测
图像分割
特征提取
immune genetic algorithm
image detection
image segmentation
feature extraction
