基于改进大津法与人工鱼群优化的图像分割算法
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Image Segmentation Algorithm Based on Improved Otsu Algorithm and Artificial Fish Swarm Optimization
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    摘要:

    为了在泡罩药品包装视觉检测过程中获取更好的图像分割效果,以保证特征提取、缺陷识别等后续任务的顺利进行,对传统二维大津法进行改进,引入类内方差并将其与人工鱼群算法相结合,提出一种新型泡罩药品包装图像分割算法,再对该算法进行理论和仿真分析。研究结果表明:该算法具有较好的图像分割效果,提高了二维阈值查找速度和泡罩药品缺陷检测效率。该算法具有运行速度快、分割效果好、准确可靠等特点,可应用于泡罩药品包装缺陷检测和图像分割领域。

    Abstract:

    Aimed at obtaining better image segmentation effect in visual inspection of blister drug packaging, so as to ensure the smooth follow-up tasks such as feature extraction and defect recognition, the traditional two-dimensional Otsu algorithm was improved and combined with the artificial fish swarm algorithm to propose a new blister medicine packaging image segmentation algorithm,with the calculation theory and simulation analysis conducted. The results showed that the algorithm performed better image segmentation effect, enhanced the two-dimensional threshold search speed and improved the efficiency of drug defect detection. The algorithm indicated the characteristics of fast running speed, good segmentation effect, accuracy and reliability, which could be applied to the detection of blister drug packaging defects and image segmentation.

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王 卓,葛 斌,涂明玉,严荣国.基于改进大津法与人工鱼群优化的图像分割算法[J].包装学报,2019,11(2):81-86.

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  • 收稿日期:2019-01-18
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  • 在线发布日期: 2019-06-13
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