Study on damaged region segmentation model of image

Huaming Liu, Yun Chen, Xuehui Bi
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引用次数: 1

Abstract

After studying the damaged region classification of Thangka image, and in light of the specific damaged situation, as for damaged region can be segmented accurately and the advantages of different image segmentation algorithms can be full played, it is proposed a damaged region segmentation model of image. Model integrates different image segmentation algorithms, the system can segment damaged regions using different algorithms according to the feature of the image damaged regions, so it can avoid looking for “universal” algorithms for segmenting image damaged regions. For the image segmentation results, it is needed to evaluate through by segmentation evaluation, at the same time, considering the error segmented region condition, here subjective evaluation is introduced in the model. The system selects algorithm, and the results of the evaluation and so on, these features are stored in the information database of image segmentation, decision-making module analysis and learning continually, and will optimize all types of segmentation algorithm in the information database. Decision-making module can make use of the historical information to guide the image damaged region segmentation, increase system segmentation efficiency and accuracy.
图像损伤区域分割模型的研究
在研究唐卡图像的损伤区域分类后,针对唐卡图像的具体损伤情况,为了能够准确分割损伤区域,充分发挥不同图像分割算法的优势,提出了一种图像损伤区域分割模型。模型集成了不同的图像分割算法,系统可以根据图像损伤区域的特点使用不同的算法分割损伤区域,从而避免了寻找图像损伤区域分割的“通用”算法。对于图像的分割结果,需要通过分割评价来进行评价,同时考虑到分割区域的误差情况,在模型中引入主观评价。系统选取算法,并对结果进行评价等,将这些特征存储在图像分割的信息库中,对决策模块进行不断的分析和学习,并将信息库中各类分割算法进行优化。决策模块可以利用历史信息来指导图像受损区域的分割,提高系统分割的效率和准确性。
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