Enhanced Ensemble Technique for Optical Character Recognition
Enhanced Ensemble Technique for Optical Character Recognition
复制标题
光学字符识别的增强集成技术
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
H. N. Abdulkhudhur
中科院分区：
文献类型：
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作者：
I. Q. Habeeb;Z. Q. Al;H. N. Abdulkhudhur
光学字符识别 (OCR) 是将图像电子转换为计算机编码文本。 OCR 系统对于噪声图像的准确性通常较差。集成识别技术用于提高 OCR 准确性。集成识别技术的思想是生成输入图像的 N 版本。这些版本相似但不相同。它们通过 OCR 引擎将其转换为不同的 OCR 输出，然后在其中选择最佳的输出。现有的集成技术需要更有效地降低 OCR 错误率。这项研究提出了增强的集成技术来克服现有技术的缺点。所提出的技术与其他三种相关的现有技术进行了评估。本研究中使用的性能测量是字错误率 (WER) 和字符错误率 (CER)。实验结果表明，与现有最佳技术的WER和CER相比，相对下降了14.37%和40.13%。这项研究对 OCR 领域做出了贡献，因为所提出的技术可以促进文档的自动识别。因此，这将导致更好的信息提取。
Optical character recognition (OCR) is the electronic transformation of images into a computer-encoded text. OCR systems often produce poor accuracy for noisy images. Ensemble recognition techniques are used to improve OCR accuracy. The idea of the ensemble recognition techniques is to produce N-versions of an input image. These versions are similar but not identical. They are passed through the OCR engine to turn them into different OCR outputs, which later leads to select the best between them. Existing ensemble techniques need to be more effective to reduce OCR error rate. This research proposed enhanced ensemble technique to overcome the drawbacks of existing techniques. The proposed technique was evaluated against three other relevant existing techniques. The performance measurements used in this research were Word Error Rate (WER) and Character Error Rate (CER). Experimental results showed a relative decrease of 14.37% and 40.13% over the WER and CER of the best existing technique. This study contributes to the OCR domain as the proposed technique could facilitate the automatic recognition of documents. Hence, it will lead to a better information extraction.