Abstract
The camera captured text images have various aspects to investigate. Generally, the emphasis of research depends on regions of interest. Sometimes the focus could be on color segmentation, object detection, or scene text analysis. The image analysis, visibility, and layout analysis are the tasks easier for humans as suggested by behavioral trait of humans, but in contrast when these same tasks are supposed to be performed by machines, then it seems to be challenging one. The learning machines always learn from the properties associated to provided samples. The numerous approaches are designed in recent years for scene text extraction and recognition, and the efforts are underway to improve the accuracy. The explicit segmentation techniques do not demonstrate reliable results. Hence, implicit segmentation techniques are pivotal for cursive text analysis. This chapter describes numerous methods and algorithms that specifically address the complexities of Arabic document and scene text analysis.
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Ahmed, S.B., Razzak, M.I., Yusof, R. (2020). Methods and Algorithm. In: Cursive Script Text Recognition in Natural Scene Images. Springer, Singapore. https://doi.org/10.1007/978-981-15-1297-1_4
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DOI: https://doi.org/10.1007/978-981-15-1297-1_4
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