Optical Character Recognition Using Active Contour Segmentation

  • Nabeel Oudah Uruk University
  • Maher Faik Esmaile Iraqi Cement State Company
  • Estabraq Abdulredaa Al-Israa College University
Keywords: OCR, active contour, Segmentation, Automatic Character Recognition, Pattern Recognition, Tesseract OCR Engine.


Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could be applied in the segmentation process. The Tesseract OCR Engine was selected in order to evaluate the performance and identification accuracy of the proposed method. The results showed that a more accurate segmentation process shall lead to a more accurate recognition results. The rate of recognition accuracy was 0.95 for the proposed algorithm compared with 0.85 for the Tesseract OCR Engine.      



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How to Cite
Oudah, N., Esmaile, M. and Abdulredaa, E. (2018) “Optical Character Recognition Using Active Contour Segmentation”, Journal of Engineering, 24(1), pp. 146-158. Available at: http://joe.uobaghdad.edu.iq/index.php/main/article/view/502 (Accessed: 24September2020).