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Alternative TitleLine Extraction Algorithms of Color Integrated Circuit Images
Thesis Advisor彭思龙
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模式识别与智能系统
Keyword彩色集成电路图像 图像分割 线提取 降维 图像融合 Color Ic Image Line Extraction Image Segmentation Dimensionality Reduction Image Fusion
Abstract线提取是集成电路(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图像的线目标和其他图像的线目标的相同点和不同点基础 上,提出了一种新的线提取方法。针对IC图像上的线目标具有方向有限,排列 密集,断裂较多,存在假线等特点,线提取被分为四步。首先在几个固定方向上 搜索局部特征点来进行初步检测,然后用区域生长来弥补在初步检测中缺损的部 分,再利用线的方向进行线区域的连接,最后用颜色信息来去掉假线。由于这种 线提取方法利用的都是IC图像比较稳定的特征,所以适用性很强,在不同批次 的IC图像的线提取中都取得了很好的效果,对于其他类型图像上的线提取也具 有很强的参考价值。 在选取彩色边缘作为线的局部几何特征进行线的检测时,本文分析了彩色边 缘提取中存在的问题。为了降低复杂度和提供一幅恰当的灰度图像对梯度方向进 行正确的指导,本文提出了两种将彩色图像变换到灰度图像的自适应变换算法。 从降维的角度出发,为了得到最优质量的灰度图像,提出了基于图像分割和加权 Fisher判据的变换算法:先对样本图像进行分割,再对衡量图像质量的加权Fisher 判据进行寻优得到最优降维方向。从图像融合的角度出发,为了在灰度图像中达 到增强特征和抑制噪声的目标,利用IC图像具有局部相似性和易于建立几何模 型两个特点,提出了基于局部线模型的变换算法:为IC图像中独特的线结构建 立了退化模型,并将基于模型的融合分为特征提取、特征增强和噪声抑制三个步 骤来进行。两种算法从两个不同角度对解决自适应彩色-灰度变换问题进行了新 的尝试,在提高灰度图像中感兴趣特征的对比度和抑制噪声上优于传统算法。
Other AbstractLine 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. A new algorithm of line extraction is proposed based on a detailed analysis of the similarity as well as difference between lines of IC images and that of other images. According to the unique traits of lines in IC images such as straight and direction-limited, densely populated, broken, having raise lines, the extraction algorithm is divided into four steps, i.e. a coarse extraction step by searching local color edge in limited directions, a refinement step to repair the missing parts in the coarse step by region growing, a linking step to connect, broken line regions of a common line based on their directions, a verification step to delete false lines utilizing color information. Since only steady features are used in the :algorithm, experiments show its good adaptability to different series of IC images. It can also be applied to other images when properly modified. Since color edges are selected as the local geometrical feature of lines in the algorithm above, to reduce the computation complexity and provide a proper gray image to guide the direction of gradient in color edge extraction, two adaptive color to gray transformation algorithms are proposed. From the viewpoint of dimensionality reduction, to get a gray image with the best quality, we firstly segment the sample image into regions, then maximize a modified version of fisher criterion acting as a image quality measure to get the optimal projection direction. From the viewpoint of image fusion, to enhance features and suppress noise in the fused image, utilizing the local similarity and easiness for geometrical modeling of IC images, a new degraded model for the unique local structures in IC images is constructed and the model-based fusion is divided into feature extraction, feature enhancement and noise suppression. The two algorithms are new attempts to solve the color to gray transformation problems from two viewpoints. Experiments show their superiority over traditional methods in enhancing the contrast of features of interest and suppressing noise of the obtained gray image.
Other Identifier760
Document Type学位论文
Recommended Citation
GB/T 7714
郭若杉. 彩色集成电路图像的线提取算法研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2004.
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