alpha-Shape Based Classification with Applications to Optical Character Recognition
- Resource Type
- Conference
- Authors
- Packer, Eli; Tzadok, Asaf; Kluzner, Vladimir
- Source
- 2011 International Conference on Document Analysis and Recognition Document Analysis and Recognition (ICDAR), 2011 International Conference on. :344-348 Sep, 2011
- Subject
- Computing and Processing
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
General Topics for Engineers
Shape
Engines
Optical character recognition software
Vectors
Support vector machine classification
Character recognition
Feature extraction
Classification
Alpha Shapes
Optical Character Recognition
- Language
- ISSN
- 1520-5363
2379-2140
We present a new classification engine based on the concept of $\alpha$-shapes. Our technique is easy to implement and use, time-effective and generates good recognition results. We show how to efficiently use the concept of $\alpha$-shapes of low dimension to support data in arbitrary dimension, thus overcoming the lack of $\alpha$-shape algorithms in high dimensions. We further show how to inelegantly choose suitable $\alpha$'s to capture desirable shapes that tightly bound the data. We present experiments showing that our technique generates good results with Optical Character Recognition (OCR) tasks. Based also on strong theoretic properties, we believe that our technique can serve as a desirable classification engine for various domains in addition to OCR.