Title :
Logos extraction on picture documents using shape and color density
Author :
Ahmed, Zeggari ; Fella, Hachouf
Author_Institution :
Comput. Sci. Dept., Univ. Center of Tebessa, Tebessa
fDate :
June 30 2008-July 2 2008
Abstract :
Logos detection on textual images is a decisive stage in documents recognition and classification system. The over or the sub-detection of logos strongly penalizes the system capacities and corrupts the subsequent stages result. We developed here an effective and robust logo extraction algorithm while considering the two principals proprieties of logos: spatial compactness and colorimetric uniformity. First, the image content is reduced and transformed using mathematical morphology operators to decrease the distance between the identical logo parts. Afterwards the logo regions of height spatial and chromatic densities are detected. The results demonstrate the robustness of the proposed method over a range of representative text images.
Keywords :
document image processing; feature extraction; image classification; image colour analysis; shape recognition; color density; colorimetric uniformity; document classification system; document recognition system; logo detection; logo extraction algorithm; mathematical morphology operator; picture document; shape density; spatial compactness; Data mining; Feature extraction; Image converters; Image databases; Image recognition; Image segmentation; Indexing; Robustness; Shape; Spatial databases; Color Density; Histogram; Logo; Mountain Function; Page Segmentation; Spatial Density;
Conference_Titel :
Industrial Electronics, 2008. ISIE 2008. IEEE International Symposium on
Conference_Location :
Cambridge
Print_ISBN :
978-1-4244-1665-3
Electronic_ISBN :
978-1-4244-1666-0
DOI :
10.1109/ISIE.2008.4677020
