An Approach for Logo Detection and Retrieval in Documents
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 te
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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. Keywords: Logo detection SIFT · PCA
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Central moments
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Human experts
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Introduction
Logos are the brand ambassadors of each and every organization whether it is a business or a government, it promotes their ideas or products with the help of the logo by investing millions of rupees on it. In every government and business document in the world has a logo which plays an important role in providing the source information of the document and in identifying the particular organization. Logo detection and recognition has become a hot topic in the Document Image Analysis and Recognition (DIAR) and pattern recognition. Computer vision methodologies and pattern recognition techniques are used in the process of automatic logo recognition and computer aided techniques makes it much easier. Logos in the document convey a lot of information like, to which organization does the document etc. Often logos come in different shapes, forms; dimensions and other complexities like, few are made of only text, graphics and in the combination of both text and graphics. These features of the logo help to c Springer Nature Singapore Pte Ltd. 2017 K.C. Santosh et al. (Eds.): RTIP2R 2016, CCIS 709, pp. 49–58, 2017. DOI: 10.1007/978-981-10-4859-3 5
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Y.H. Sharath Kumar and K.C. Ranjith
differentiate from other content in the body of the document. Features of logo contribute in logo detection, retrieval and matching in document.
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Literature Survey
Here we review the papers that related to logo detection and retrieval. Viet et al. [1] have presented methodology for digital document categorization based on logo spotting. The logos are recognized using key point matching. Initially, the logos are segmented using spatial density-based clustering. Stefan et al. [2] have proposed a highly effective and scalable framework for recognizing logos in images. Alireza et al. [3] proposed a coarse-to-fine logo detection scheme for document images. The content of a document image is pruned by utilizing a decision tree. The Nearest Neighbour (N
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