Title :
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
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;
Conference_Titel :
Intelligent Computation and Bio-Medical Instrumentation (ICBMI), 2011 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-1-4577-1152-7
DOI :
10.1109/ICBMI.2011.26
