The METU Dataset is a large dataset (the largest publicly available logo dataset as of 2014), which is composed of more than 900K real logos belonging to real companies worldwide. The dataset also includes query sets of varying difficulties, allowing Trademark Retrieval researchers to benchmark their methods against other methods to progress the field.
The Dataset includes 930,053 logo images of different types: text only logos, figure only logos and text+figure combined logos. See Figure 1 for samples.
Figure 1: trademark samples from main dataset
Our dataset includes very challenging queries that existing Computer Vision, Pattern Recognition and Image Retrieval methodologies have difficulties with (study is ongoing). See Figure 2 or query_set for some sample queries and similarities that are expected to be discovered.
Table 1: Details of METU dataset
|unique register firms||409,834|
|trademarks containing text only||589,562|
|trademarks containing figure only||19,394|
|trademarks containing figure and text||312,154|
The literature already has a few logo datasets: MPEG 7 Shape Matching Dataset, UMD Logo Dataset, UMD Logo Dataset , Tobacco800 Document Image Database . Although these datasets have been very useful in logo retrieval and matching studies, they are limited in the number of images and the types of queries that can be performed - see Table 2. Therefore, to be able to advance the logo retrieval field, a challenging large dataset is required, and we hope that METU Dataset will fill in this gap.
Table 2: Comparison of existing logo datasets.
|Logo dataset||Number of images|
|MPEG 7 Shape Matching Dataset||1,400|
|UMD Logo Dataset||106|
|Tobacco800 Document Image Database||1,290|
|METU Dataset (This set)||930,053|
Figure 2: similar trademark set samples from query dataset
For the time being, the dataset is available per request only. If you are interested in the dataset for research purposes, please contact Sinan Kalkan with your intention.
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Please cite the following paper if you use this dataset:
O. Tursun, S. Kalkan, "A Challenging Big Dataset for Benchmarking Trademark Retrieval", 14th IAPR Conference on Machine Vision and Applications, 2015.