Ocr using pca
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OCR using PCA. Ohad klausner. Introduction. What is OCR?? Optical character recognition. What is PCA???? principal components analysis reducing dimnesionalty in a dataset retaining characteristics of the dataset. Why PCA?. Appearance based recognition Suited for OCR

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OCR using PCA

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Ocr using pca

OCR using PCA

Ohad klausner


Introduction

Introduction

  • What is OCR??

    • Optical character recognition

  • What is PCA????

    • principal components analysis

      • reducing dimnesionalty in a dataset

      • retaining characteristics of the dataset


Why pca

Why PCA?

  • Appearance based recognition

    • Suited for OCR

  • optimal linear transformation subspace

    • Less compution time

    • Minimal lose of accuracy


Why not problems

Why not? (problems….)

  • Poor recognition rate: 50%

  • Two main problems:

    • Location sensitivity:

      • image: recognized as:

  • Similar letters:

    • image: recognized as:

      Kaph Sofit Resh


Ocr enhancements

OCR enhancements

  • Choosing k

    • Accuracy and compution time tradeoff

  • Creating a whole word OCR

    • minimizes the similar letters mistake

  • Centering the letters

    • Solves location sensitivity problem


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