TY - GEN
T1 - Categorization of camera captured documents based on logo identification
AU - Edupuganti, Venkata Gopal
AU - Shih, Frank Y.
AU - Kompalli, Suryaprakash
PY - 2011
Y1 - 2011
N2 - In this paper, we present a methodology to categorize camera captured documents into pre-defined logo classes. Unlike scanned documents, camera captured documents suffer from intensity variations, partial occlusions, cluttering, and large scale variations. Furthermore, the existence of non-uniform folds and the lack of document being flat make this task more challenging. We present the selection of robust local features and the corresponding parameters by comparisons among SIFT, SURF, MSER, Hessian-affine, and Harris-affine. We evaluate the system not only with respect to amount of space required to store the local features information but also with respect to categorization accuracy. Moreover, the system handles the identification of multiple logos on the document at the same time. Experimental results on a challenging set of real images demonstrate the efficiency of our approach.
AB - In this paper, we present a methodology to categorize camera captured documents into pre-defined logo classes. Unlike scanned documents, camera captured documents suffer from intensity variations, partial occlusions, cluttering, and large scale variations. Furthermore, the existence of non-uniform folds and the lack of document being flat make this task more challenging. We present the selection of robust local features and the corresponding parameters by comparisons among SIFT, SURF, MSER, Hessian-affine, and Harris-affine. We evaluate the system not only with respect to amount of space required to store the local features information but also with respect to categorization accuracy. Moreover, the system handles the identification of multiple logos on the document at the same time. Experimental results on a challenging set of real images demonstrate the efficiency of our approach.
KW - Logo detection
KW - affine-invariant features
KW - clustering
KW - hamming embedding
UR - http://www.scopus.com/inward/record.url?scp=80052812318&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80052812318&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-23678-5_14
DO - 10.1007/978-3-642-23678-5_14
M3 - Conference contribution
AN - SCOPUS:80052812318
SN - 9783642236778
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 130
EP - 137
BT - Computer Analysis of Images and Patterns - 14th International Conference, CAIP 2011, Proceedings
T2 - 14th International Conference on Computer Analysis of Images and Patterns, CAIP 2011
Y2 - 29 August 2011 through 31 August 2011
ER -