Abstract
Detection and Retrieval of logos in document images has become a fundamental concept in the Document Image Analysis and Recognition (DIAR). In this work, we propose a system to identify logos from a given document. The approach initially eliminates the text and later the logos are extracted from the remaining contents through proposed logo detection algorithm using central moments. For detected logos, the scale invariant feature transforms are extracted and the extracted features are reduced using principle component analysis (PCA). For effective retrieval of logos, an indexing mechanism called k-d tree is used. In order to substantiate the efficacy of the proposed model experimentation is conducted based on a dataset over 500 various samples such as conference certificates, degree certificates, attendance certificates, etc. Further, to study the efficiency of the proposed method we have compared the obtained results with the results provided by five human experts and the results are more encouraging.
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Sharath Kumar, Y.H., Ranjith, K.C. (2017). An Approach for Logo Detection and Retrieval in Documents. In: Santosh, K., Hangarge, M., Bevilacqua, V., Negi, A. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2016. Communications in Computer and Information Science, vol 709. Springer, Singapore. https://doi.org/10.1007/978-981-10-4859-3_5
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DOI: https://doi.org/10.1007/978-981-10-4859-3_5
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