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Genetic approach to the analysis of complex text formatting,

机译:遗传方法分析复杂的文本格式,

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Abstract: Traditional document analysis systems often adopt a top-down framework, i.e., they are composed of various locally interacting functional components, guided by a central control mechanism. The design of each component is determined by a human expert and is optimized for a given class of inputs. Such a system can fail when confronted by an input that falls outside its anticipated domain. This paper investigates the use of a genetic-based adaptive mechanism in the analysis of complex test formatting. Specifically, we explore a genetic approach to the binarization problem. As opposed to a single, pre-defined, 'optimal' thresholding scheme, the genetic-based process applies various known methods and evaluates their effectiveness on the input image. Individual regions are treated independently, while the genetic algorithm attempts to optimize the overall result for the entire page. Advantages and disadvantages of this approach are discussed. !12
机译:摘要:传统的文档分析系统通常采用自上而下的框架,即由中央控制机制指导的各种本地交互功能组件组成。每个组件的设计均由专家确定,并针对给定的输入类别进行了优化。当遇到超出其预期范围的输入时,这样的系统可能会失败。本文研究了基于遗传的自适应机制在复杂测试格式分析中的使用。具体来说,我们探索一种解决二值化问题的遗传方法。与单个预定义的“最佳”阈值方案相反,基于遗传的过程应用了各种已知方法,并评估了它们在输入图像上的有效性。单个区域被独立对待,而遗传算法则尝试优化整个页面的总体结果。讨论了这种方法的优缺点。 !12

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