Abstract
The detection and extraction of text regions in an image is a well known problem in the computer vision research area. The goal of this project is to compare two basic approaches to text extraction in natural (non-document) images: edge-based and connected-component based. The algorithms are implemented and evaluated using a set of images of natural scenes that vary along the dimensions of lighting, scale and orientation. Accuracy, precision and recall rates for each approach are analyzed to determine the success and limitations of each approach. Recommendations for improvements are given based on the results.
Publication Date
2007
Document Type
Master's Project
Student Type
Graduate
Degree Name
Computer Science (MS)
Department, Program, or Center
Computer Science (GCCIS)
Advisor
Canosa, Roxanne
Advisor/Committee Member
Raj, Rajendra
Advisor/Committee Member
Bischof, Hans-Peter
Recommended Citation
Sharma, Sneha, "Extraction of text regions in natural images" (2007). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/162
Campus
RIT – Main Campus
Comments
Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in December 2013.