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A brief introduction to OCR (Optical character recognition)

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These slides include the answers for the following questions:
- What is OCR?
- Why do we need it?
- Why is it difficult?
- Comparison between OCR & object detections
- Three approaches for text localization
- Three approaches for text recognition

Videos are also available from the below:
(Korean) https://youtu.be/ckRFBl_XWFg
(English) coming soon

[Reference] Hwalsuk Lee, https://www.slideshare.net/deview/111-ai

Published in: Engineering
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A brief introduction to OCR (Optical character recognition)

  1. 1. Terry Taewoong Um fb.com/deeplearningtalk fb.com/terryum 사진 속 글자를 읽어주는 Optical Character Recognition (OCR) 42
  2. 2. What is OCR? • Optical Character Recognition (OCR) Reading typed/printed/handwritten characters from image sources Speech Recognition
  3. 3. What is OCR? • Optical Character Recognition (OCR) Reading typed/printed/handwritten characters from image sources OCR
  4. 4. Why OCR? characters in the computer characters in the physical world A
  5. 5. Why OCR? characters in the computer characters in the physical world Difficult because of the large variations! (font, size, shape, location, noise, ...)
  6. 6. OCR vs Object detection Text Localization Text Recognition • OCR • Object detection Object Localization Object Recognition Detect the bounding boxes that enclose text Read it • OCR is more challenging than object detection due to - various aspect (W:H) ratio - large distortions - confusion w/ textures (‘I’, ‘T’) - few pretrained models- high density - various languages
  7. 7. Text Localization Text Localization Text Recognition 이활석, https://www.slideshare.net/deview/111-ai regression-based (like object detection) end-to-end [Textboxes, Liao et al., AAAI2017] [PixelLink, Deng et al., AAAI2018] classification-based (like semantic segmentation) [FOTS, Liu et al., CVPR2018] simultaneous local+recog # of papers training unstable stable
  8. 8. Text Recognition Text Localization Text Recognition Connectionist Temporal Classification r EOSpt i t pi<GO> r Attention # of papers speed rarely used accuracy
  9. 9. OCR + Translation = SmartLens Text Localization Text Recognition Machine translation • What you need to know is - Machine learning basics - Neural network basics - Convolutional Neural Networks (+ advanced topics) - Recurrent Neural Networks (+ advanced topics)

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