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Petroglyph Recognition Using Self-Organizing Maps and Fuzzy Visual Language Parsing

机译:自组织映射和模糊视觉语言解析的岩画文字识别

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Petroglyphs are images carved into a rock surface by prehistoric people using a symbolic or ritual language. Although they constitute an historical patrimony of inestimable value, little efforts have been devoted to the development of automated tools for their classification and interpretation. In this work we present a new algorithm for recognizing petroglyphs within scenes composed of several engraved figures. The proposal combines an unsupervised recognizer, Self-Organizing Maps (SOM), with a fuzzy visual language parser. The first classifies the petroglyph symbols extracted from a scene by using Radon transform as shape descriptor. The latter exploits the archeological knowledge about recurring patterns within scenes to solve ambiguous interpretations. The algorithm has been evaluated on a set of 50 petroglyph scenes, containing about 500 carved symbols from Mount Bego rock art site, and achieved very promising results.
机译:岩画是史前人们使用象征或仪式语言刻在岩石表面上的图像。尽管它们构成了具有不可估量价值的历史遗产,但很少有人致力于开发用于对其分类和解释的自动化工具。在这项工作中,我们提出了一种新的算法,用于识别由多个雕刻图形组成的场景中的岩画。该提案结合了无监督识别器,自组织映射(SOM)和模糊视觉语言解析器。第一种通过使用Radon变换作为形状描述符对从场景中提取的岩画符号进行分类。后者利用有关场景中重复模式的考古学知识来解决模棱两可的解释。该算法已在50个岩画场景中进行了评估,其中包含来自Bego山岩石艺术遗址的约500个雕刻符号,并取得了非常可喜的结果。

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