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集成电路图像有源区分割方法
Alternative TitleSource area Segmentation of Integrated Circuit Images
刘佳璐
Subtype工学博士
Thesis Advisor彭思龙
2006-06-03
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
Keyword集成电路图像 图像分割 分水线变换 Map算法 图像分解 纹理分割 Ic Image Image Segmentation Object Extraction Watershed Transform Map Algorithm Image Decomposition
Abstract集成电路的有源区图像的提取是集成电路(Integrated Circuit, IC)图像处理中最重要的任务之一,是一个针对特定图像的图像分割问题,要达到准确、快速的分割,必须充分结合IC图像的特点,综合采用各种分割技术。 我们在分析了IC图像的有源区和走线目标和其他图像的目标方法的基础上,提出了两种新提取算法。我们先提出一种基于数字形态学分水线基础上的贝叶斯图像分割方法。即对首先原始集成电路图像使用分水线算法,进行预分割,然后在分割后的子区域上,采用基于先验知识的贝叶斯分割方法,我们设计一个先验密度来惩罚图像当中分水线变换后的相似的区域,图像分割进而变成对目标子集的最大后验估计。这样就可以逐步的找出最理想目标区域和背景区域,这一算法的提出,一方面可以有效解决分水线图像的过分割问题,另一方面,也解决了传统基于先验知识的分割方法所出现的计算量巨大的问题。这个算法后来直接应用在几个不同的自然图像中。 我们随后将这一方法应用到彩色空间中。在一些彩色图像中,由于保持比较丰富的彩色信息,不适合直接转化成灰度后,再进行分割处理任务。我们在彩色图像基础上直接进行分水线变换,然后在分水线后的过分割图像上,使用基于彩色空间信息的贝叶斯图像分割方法,对过分割结果进行融合处理。这种算法在提高彩色图像中目标识别上优于传统灰度算法。 在文章的第五章,认真的研究了图像分解在纹理区域分割中的应用。我们通过图像分解的方法把纹理图像分解成为两部分作为特征通道用于一种基于先验知识的纹理图像分割方法中,提出一种新的基于图像分解的无监督纹理图像分割方法。
Other AbstractSource area extraction is one of the most important tasks in IC (Integrated Circuits) image processing. It is a problem of image segmentation on specialized images whose special characteristic must be taken into account during segmentation to ensure an accurate and fast result. We present tow new algorithm based on analyzed the character similarity as well as difference between that of source area of IC images. We present a Image Segmentation algorithm based on Watershed and prior knowledge. Frist of all we transform the original image to watershed then we calculate the energy of the label image result from the Watershed  transform by designing a prior density that penalizes the area of homogeneous parts in images . The segmentation problem is the maximizing a posteriori estimation(MAP) of the set of areas such we can find the optimal areas of object, and the other areas of the image are looked as background areas . The experiments indicate our Algorithm is effective for IC image segmentation. Then we extend this algorithm into RGB space. In some of the color images didn’t adapt to process after transforming to gray image for it will lost some important information. We use the color image as original image transform to watershed image, than we use a news 3-D prior knowledge find the optimal object area. This algorithm not only solved the oversegmentation problems of watershed transform ,but also used color information and prior knowledge. The experiments indicate our Algorithm is effective for image segmentation. In the last Section , we present a new texture segmentation base on image decomposition . we use a new textural feature and smooth feature as feature channel based on image decomposition technology,then we use them in a unsupervised texture segmentation method.
shelfnumXWLW1047
Other Identifier200118014604873
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/5934
Collection毕业生_博士学位论文
Recommended Citation
GB/T 7714
刘佳璐. 集成电路图像有源区分割方法[D]. 中国科学院自动化研究所. 中国科学院研究生院,2006.
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