Title
Fast and Accurate Handwritten Character Recognition Using Approximate Nearest Neighbours Search on Large Databases
Abstract
In this work, fast approximate nearest neighbours search algorithms are shown to provide high accuracies, similar to those of exact nearest neighbour search, at a fraction of the computational cost in an OCR task. Recent studies [26,15] have shown the power of k-nearest neighbour classifiers (k-nn) using large databases, for character recognition. In those works, the error rate is found to decrease consistently as the size of the database increases. Unfortunately, a large database implies large search times if an exhaustive search algorithm is used. This is often cited as a major problem that limits the practical value of the k-nearest neighbours classification method. The error rates and search times presented in this paper prove, however, that k-nn can be a practical technique for a character recognition task.
Year
DOI
Venue
2000
10.1007/3-540-44522-6_79
SSPR/SPR
Keywords
Field
DocType
approximate nearest neighbours search,large database,exhaustive search algorithm,accurate handwritten character recognition,large databases,character recognition,search time,error rate,large search time,ocr task,neighbour search,handwriting recognition
Nearest neighbour search,Nearest neighbour,Search algorithm,Character recognition,Computer science,Word error rate,Handwriting recognition,Exhaustive search algorithm,Database
Conference
Volume
ISSN
ISBN
1876.0
0302-9743
3-540-67946-4
Citations 
PageRank 
References 
12
0.98
26
Authors
3
Name
Order
Citations
PageRank
Juan C. Pérez-Cortés113716.20
Rafael Llobet2728.78
Joaquim Arlandis3859.92