1 / 5

OCR using PCA

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

kael
Télécharger la présentation

OCR using PCA

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. OCR using PCA Ohad klausner

  2. Introduction • What is OCR?? • Optical character recognition • What is PCA???? • principal components analysis • reducing dimnesionalty in a dataset • retaining characteristics of the dataset

  3. Why PCA? • Appearance based recognition • Suited for OCR • optimal linear transformation subspace • Less compution time • Minimal lose of accuracy

  4. Why not? (problems….) • Poor recognition rate: 50% • Two main problems: • Location sensitivity: • image: recognized as: • Similar letters: • image: recognized as: Kaph Sofit Resh

  5. 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

More Related