Abstract
Text recognition is significantly influenced by font types, especially for complex scripts like Khmer. The variety of Khmer fonts, each with its unique character structure, presents challenges for optical character recognition (OCR) systems. In this study, we evaluate the impact of 19 randomly selected Khmer font types on text recognition accuracy using Pytesseract. The fonts include Angkor, Battambang, Bayon, Bokor, Chenla, Dangrek, Freehand, Kh Kompong Chhnang, Kh SN Kampongsom, Khmer, Khmer CN Stueng Songke, Khmer Savuth Pen, Metal, Moul, Odor MeanChey, Preah Vihear, Siemreap, Sithi Manuss, and iSeth First. Our comparison of OCR performance across these fonts reveals that Khmer, Odor MeanChey, Siemreap, Sithi Manuss, and Battambang achieve high accuracy, while iSeth First, Bayon, and Dangrek perform poorly. This study underscores the critical importance of font selection in optimizing Khmer text recognition and provides valuable insights for developing more robust OCR systems.
Abstract (translated)
文本识别在很大程度上受到字体类型的影响，尤其是在处理像高棉语这样复杂的脚本时。由于每种高棉语字体都有其独特的字符结构，这给光学字符识别（OCR）系统带来了挑战。在这项研究中，我们使用Pytesseract评估了19种随机选择的高棉语字体对文本识别准确率的影响。这些字体包括Angkor、Battambang、Bayon、Bokor、Chenla、Dangrek、Freehand、Kh Kompong Chhnang、Kh SN Kampongsom、Khmer、Khmer CN Stueng Songke、Khmer Savuth Pen、Metal、Moul、Odor MeanChey、Preah Vihear、Siemreap、Sithi Manuss和iSeth First。我们对这些字体的OCR性能进行了比较，结果显示Khmer、Odor MeanChey、Siemreap、Sithi Manuss以及Battambang字体实现了较高的准确率，而iSeth First、Bayon和Dangrek的表现较差。这项研究表明，在优化高棉语文本识别中选择合适的字体至关重要，并为开发更强大的OCR系统提供了宝贵的见解。
URL
https://arxiv.org/abs/2506.23963
