@inproceedings{435d5a7827e349caacb6bd1277472f31,
title = "A fuzzy color classification for logos retrieval",
abstract = "A fuzzy color classification for logos retrieval scheme is developed to retrieve logos efficiently. We transfer each logo to only 8 colors image using only 8 rules. Afterwards, we utilize the 8 colors images for comparing the logos. The major differences between our proposed method and existing ones are: 1. We consider the spatial information. (Our approach is permutation comparison). Most of the existing ones (color classification-based methods) are combination comparison. 2. We resized all images to 40 X 30 pixels. Therefore, our approach can handle diverse sizes, defocus and noise problems. 3. We adopt the concept of the relative relation of RGB. Consequently, our system can deal with dissimilar lighting conditions, partial occlusion, and various color saturation at the same time. 4. We don't want to know what the meanings of the logos are. We do want to know what the colors of the logos are.",
keywords = "Color classification, Content-based images retrieval (CBIR), logos retrieval",
author = "Chiunhsiun Lin and Su, {Ching Hung} and Lu, {Tzu Ying} and Hsuanshu Huang and Fan, {Kuo Chin} and Hsieh, {Tsai Ming}",
year = "2013",
doi = "10.1109/iFuzzy.2013.6825451",
language = "???core.languages.en_GB???",
isbn = "9781479903863",
series = "iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications",
publisher = "IEEE Computer Society",
pages = "283--287",
booktitle = "iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications",
note = "iFUZZY 2013 - 2013 International Conference on Fuzzy Theory and Its Applications ; Conference date: 06-12-2013 Through 08-12-2013",
}