Paper Info
Title
Text Line Detection in Document Images: Towards a Support System for the Blind
Abstract
We introduce a novel approach for text line detection in document images, keeping in mind the requirements of a portable text recognition system designed to support the blind. Challenges include shadows, cluttered backgrounds, and perspective distortion. Different from previous approaches, the proposed method does not segment the image. A text model is created by clustering SIFT features extracted from positive and negative examples. Text regions are located by matching the features extracted from the input image to the clusters in the text model. Regions around the correspondences are then analyzed, and text lines are identified based on features such as gradients and histogram distribution. Experimental results show that our approach outperforms a state-of-the-art text detector in a text/non-text classification task.
Year
DOI
Venue
2013
10.1109/ICDAR.2013.131
ICDAR-1
Keywords
Field
DocType
document image processing,feature extraction,handicapped aids,image classification,image matching,object detection,SIFT feature clustering,blind support system,classification task,cluttered backgrounds,document image,feature extraction,feature matching,gradients,histogram distribution,perspective distortion,portable text recognition system,scale-invariant feature transform,shadows,text line detection,Document Image Processing,Text Detection
Object detection,Histogram,Computer vision,Pattern recognition,Feature detection (computer vision),Feature (computer vision),Computer science,Document layout analysis,Feature extraction,Artificial intelligence,Cluster analysis,Contextual image classification
Conference
ISSN
Citations 
PageRank 
1520-5363
1
0.35
References 
Authors
5
3
Name
Order
Citations
PageRank
Bogdan Tomoyuki Nassu1215.39
Rodrigo Minetto217815.01
Luiz Eduardo Soares De Oliveira3121.96