【作者】 谭晓东；

【导师】 罗三定；

【作者基本信息】 中南大学 ， 计算机应用技术， 2007， 硕士

【摘要】 数字图像处理技术作为一门专门的研究学科出现以来，其应用已经从最初的工业及商业领域扩展到艺术、文化等领域以及人们的日常生活中。图像匹配是图像识别系统中必不可少的重要环节，也是图像处理中最常见和困难的问题之一。本课题主要针对多值模板匹配方法及其相关的问题进行研究，主要包括以下几个方面。模板图像分割方面，首先本文提出了对模板多值化的基于灰度的分割方法，将寻找最优阈值过程建模为寻找使分割后图像与源图像相似度最大阈值集合过程，利用模板匹配公式作为相似度评价标准，并提出了与模板匹配等价的基于直方图的分割算法，理论和实验结果表明，新算法有很好的分割效果，再从非线形规划的角度对最佳阈值的选取过程进行了优化，进一步提高了分割速度。然后提出了基于图像边缘特征为模板多值分割方法，提出了边缘偏离程度的概念，将寻找最优阈值过程建模为寻找使分割后图像与源图像边缘偏离程度最小的阈值集合过程。最后本文将提出的割方法推广到对一般图像的分割，并与OTSU方法，最大熵方法进行了比较。快速图像匹配算法方面，本文提出了基于多值模板的图像快速匹配算法，即将最佳多阈值分割后的模板图像作为新的模板进行图像匹配，利用差值模板中存在的大量灰度变化相同区域，采用迭代的方法，减少这些区域的计算，从而减小复杂度，实验得到了比较满意的结果，最后提出了匹配差异的概念，对多值模板匹配结果和源模板的匹配结果差异进行衡量。最佳阈值个数选取方面，本文提出了模板图像最佳分割阈值个数的衡量标准和选取条件，目的是用较少的阈值数对源模板进行分割，保证快速匹配的低复杂度和匹配精度。然后研究了不同的图像分割方法对阈值个数的影响，以及阈值个数的选取和模板图像本身特性的关系等相关问题。更多还原

【Abstract】 Since digital image processing has been a special subject, it was applied in several fields from the initial industry and commerce to the art, culture and people’s daily life. The image mate are indispensable components in the pattern recognition system, and it was also one of the most difficult and commonly problem. This topic mainly aims is to research the multi-value template matching method and the key question, Main content include following several aspects.In template image segmentation. First, this text proposed the segmentation algorithm which based on gradation to segment template, this threshold segmentation algorithm which transform the process of finding optimal threshold to the process of finding maximal likeness degree with optimal threshold between source picture and after segmentation picture. Taking the template matches formula as the standards of the evaluating likeness degree, and designing a segmentation algorithm based on the histogram which equivalent the template matching. The theoretical and experiment results showed that the new method has good dissection effect, and the speed is quick. Then the text put forward the segmentation algorithm which based on edge to segment template, put forward the concept of edge deviation degree . Finally, this text propose the method to promote to the general picture segmentation.In fast image matching, this text put forward the fast-matching method which base on the multi-value template, made the template picture which have been segmented as new template to match image, then utilized the same district of D-template and use a iteration method to reduce the calculation. The experiment got the more satisfied result. Finally, put forward the match difference concept and carry on measuring to the difference between the result of multi-value template matching and Source template matching.In the optimal number of threshold, this text chose the standards of how to get the number of image optimal threshold, Selected the best number of threshold to segment source template, Guarantees the low complex in fast matching. Then it has research the different segmentation method to the number of optimal threshold and the relationship betweentemplate characteristic and choice of optimal threshold .更多还原