[author_cn_name].[cn_title][J].空军工程大学学报:自然科学版,[year_id],[volume]([issue]):[start_page]-[end_page] 一种不同色域空间下的无监督图像分割技术- A Kind of Unsupervised Segmentation Technique in Different Color Space
吴涛, 王伦武, 王伦文, 朱敬成.一种不同色域空间下的无监督图像分割技术[J].空军工程大学学报:自然科学版,2022,23(1):104-111
A Kind of Unsupervised Segmentation Technique in Different Color Space
中文关键词: 色域空间  超像素  图像分割  无监督学习
英文关键词: color space  super pixel  image segmentation  unsupervised learning
吴涛, 王伦武, 王伦文, 朱敬成 国防科技大学电子对抗学院合肥230037 
摘要点击次数: 87
全文下载次数: 104
      Aimed at the problems that the supervised learning model for image segmentation is long in training time, a large number of training samples is needed to ensure model accuracy requirement, and the labeling takes a lot of work, time and energy, an unsupervised image segmentation method is proposed based on neural network in different color space. Firstly, the images are transformed into different color space models to obtain the color representation of images in different color gamut spaces, and then by using felz and quickshift methods, a coarse grained cluster is made after the images being transformed to form super pixel results and label each pixel accordingly. Finally, the fine grained image feature discrimination ability of neural networks is utilized for making a fine turning, obtaining the final image segmentation results. The method is validated on publicly available datasets such as COD10K selected, and the experiments prove that the proposed method can segment images reasonably with less inference time consumption and faster speed in comparison with the supervised training for a long time.
查看全文   查看/发表评论  下载PDF阅读器