An introduction to digital image processing
An introduction to digital image processing
A new method for image segmentation
Computer Vision, Graphics, and Image Processing
Extraction of binary character/graphics images from grayscale document images
CVGIP: Graphical Models and Image Processing
Evaluation of Binarization Methods for Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Character image enhancement by selective region-growing
Pattern Recognition Letters
A Lexicon Driven Approach to Handwritten Word Recognition for Real-Time Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Document Binarization
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Binarising Camera Images for OCR
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Handwriting Analysis of Pre-Hospital Care Reports
CBMS '04 Proceedings of the 17th IEEE Symposium on Computer-Based Medical Systems
Global Shape Normalization for Handwritten Chinese Character Recognition: A New Method
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Indexing and searching handwritten medical forms
dg.o '06 Proceedings of the 2006 international conference on Digital government research
Indexing and retrieval of handwritten medical forms
dg.o '07 Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains
Processing and retrieving handwritten medical forms
dg.o '08 Proceedings of the 2008 international conference on Digital government research
A probabilistic method for keyword retrieval in handwritten document images
Pattern Recognition
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This paper presents a methodology for separating handwritten foreground pixels, from background pixels, in carbon copied medical forms. Comparisons between prior and proposed techniques are illustrated. This study involves the analysis of the New York State (NYS) Department of Health (DoH) Pre-Hospital Care Report (PCR) [1] which is a standard form used in New York by all Basic and Advanced Life Support pre-hospital healthcare professionals to document patient status in the emergency environment. The forms suffer from extreme carbon mesh noise, varying handwriting pressure sensitivity issues, and smudging which are further complicated by the writing environment. Extraction of handwriting from these medical forms is a vital step in automating emergency medical health surveillance systems.