A Fast Logo Recognition Algorithm in Noisy Document Images

Author

Hassanzadeh, Sina ; Pourghassem, Hossein

Author_Institution

Dept. of Electr. Eng., Islamic Azad Univ., Najafabad, Iran

fYear

2011

fDate

14-17 Dec. 2011

Firstpage

64

Lastpage

67

Abstract

Logo recognition is one of the applied aspects of graphic recognition domain. In most of document images, some diverse conditions such as noise existence, occlusion, and different scale/orientation may affect logo recognition process. In this paper, a novel approach based on spatial and structural features of logo images is proposed to overcome those problems. After normalization step which eliminates the sensitivity of the logo recognition process to different scale/orientation, a novel feature is extracted based on horizontal and vertical histograms of the logo image. Finally, KNN classifier is used to recognize logo images. Our proposed algorithm is evaluated on a standard logo dataset of Maryland University. The experimental results show the robustness of the proposed approach in the logo recognition.

Keywords

document image processing; feature extraction; image classification; statistical analysis; KNN classifier; feature extraction; graphic recognition domain; horizontal histogram; k-nearest neighbor; logo recognition algorithm; noisy document image; normalization step; vertical histogram; Classification algorithms; Feature extraction; Histograms; Image recognition; Image segmentation; Noise measurement; Pattern recognition; KNN classification; feature extraction; horizontal and vertical histograms; logo image normalization; logo recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation and Bio-Medical Instrumentation (ICBMI), 2011 International Conference on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-1-4577-1152-7

Type

conf

DOI

10.1109/ICBMI.2011.26

Filename

6131705