18. Applicaton example: Photo OCR

Applicaton example: Photo OCR

Problem description and pipeline

Photo OCR pipeline：

1. Text detection
2. Character segmentation
3. Character classification

Sliding windows

Text detection:

sliding window detection:

• step-size/stride

Character segmentation:

1D Sliding window for character segmentation

Getting lots of data: Artificial data synthesis

• Create new data.
• Synthesizing data by introducing distortions
  • Distortion introduced should be representation of the type of noise/distortions in the test set.
  • Usually does not help to add purely random/meaningless noise to your data.

Ceiling analysis: What part of the pipeline to work on next

Estimating the errors due to each compoent

What part of the pipeline should you spend the most time trying to improve?