Paper Info
Title
Cloud of Line Distribution for Arbitrary Text Detection in Scene/Video/License Plate Images.
Abstract
Detecting arbitrary oriented text in scene and license plate images is challenging due to multiple adverse factors caused by images of diversified applications. This paper proposes a novel idea of extracting Cloud of Line Distribution (COLD) for the text candidates given by Extremal regions (ER). The features extracted by COLD are fed to Random forest to label character components. The character components are grouped according to probability distribution of nearest neighbor components. This results in text line. The proposed method is demonstrated on standard database of natural scene images, namely ICDAR 2015, video images, namely ICDAR 2015 and license plate databases. Experimental results and comparative study show that the proposed method outperforms the existing methods in terms of invariant to rotations, scripts and applications.
Year
DOI
Venue
2017
10.1007/978-3-319-77380-3_41
ADVANCES IN MULTIMEDIA INFORMATION PROCESSING - PCM 2017, PT I
Keywords
Field
DocType
Extremal regions,Text candidates,COLD,Text detection,License plate detection
k-nearest neighbors algorithm,Computer vision,Pattern recognition,Computer science,Probability distribution,Invariant (mathematics),Artificial intelligence,Random forest,Text detection,License,Scripting language,Cloud computing
Conference
Volume
ISSN
Citations 
10735
0302-9743
0
PageRank 
References 
Authors
0.34
19
5
Name
Order
Citations
PageRank
Wenhai Wang1739.45
Yirui Wu2137.14
Palaiahnakote Shivakumara377464.90
tong lu437267.17
Jun Liu567130.44