Abstract
Comic document image analysis is now an active field of research in both academia and industry. However, comic document image processing research suffers due to its inherent complexities and the limited availability of benchmark public datasets. This paper describes the creation of the first-ever comic dataset among Indian Languages, namely Bangla Comic Book Image dataset (BCBId) (https://sites.google.com/view/banglacomicbookdataset), which is also made public for the benefit of the researchers. BCBId consists of 3327 images taken from 64 Bangla comic stories written by 8 writers. Bangla is the 6th most popular spoken language in the world—used by 265 million people (https://en.wikipedia.org/wiki/Languages_of_India), and has a century-old heritage of comic strips (in newspapers) and books. BCBId has the ground truth for extracting various visual components of the comic book images, i.e., panels, characters, speech balloons, and text lines. BCBId also includes the metadata encoding of all images in XML format to describe the underlined structure, semantics, and other features of the documents to pursue research on understanding stories and dialogues. A tool is specifically designed for accurate and faster ground-truth generation. As an application of the dataset, we carry out the sentiment analysis of comic stories—the first-ever attempt on comic book images. We also elaborate on a couple of applications of the BCBId in the comic research domain. Besides, we estimate the errors made by the annotators during the annotation process and describe different evaluation parameters to test the efficacy of the comic document image analysis algorithms.
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Dutta, A., Biswas, S. & Das, A.K. BCBId: first Bangla comic dataset and its applications. IJDAR 25, 265–279 (2022). https://doi.org/10.1007/s10032-022-00412-9
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DOI: https://doi.org/10.1007/s10032-022-00412-9