Modeling human color categorization
Pattern Recognition Letters
Detecting Gradients in Text Images Using the Hough Transform
DAS '08 Proceedings of the 2008 The Eighth IAPR International Workshop on Document Analysis Systems
Color Transfer in Images Based on Separation of Chromatic and Achromatic Colors
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
Color image segmentation by analysis of subset connectedness and color homogeneity properties
Computer Vision and Image Understanding
Data clustering: 50 years beyond K-means
Pattern Recognition Letters
Color histogram-based image segmentation
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Chromatic / Achromatic Separation in Noisy Document Images
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
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This paper addresses the problem of color documents images segmentation in an industrial context. Automated Document Recognition (ADR) systems highly reduce time and resource costs of companies by managing their huge amount of administrative documents, and by optimizing their workflow. Most of the time, a binarization is performed due to their historical industrial process. Therefore, colorimetric information can improve the process. In this paper, we propose a hierarchical clustering based approach to extract dominant color masks of documents. Indeed, our dataset comprises different kind of scanned administrative document images such as invoices, forms, letters, and so on. We do not know a priori the number of dominant colors on our documents. These masks will further feed the inputs to an OCR in order to bring extra-information about the colorimetric context. This approach requires neither user interaction nor setting steps. Experiments on several types of documents show the relevance of the proposed approach