Abstract
Digital Image Analysis is one of the most challenging and important tasks in many scientific and engineering applications. The two vital subtasks in image analysis are recognition and extraction of object(s) of interest (OOI) from an image. When these tasks are manually performed, it calls for human experts, making them more time consuming, more expensive and highly constrained. These negative factors led to the development of various computer systems performing an automatic recognition and extraction of visual information to bring consistency, efficiency and accuracy in image analysis. This paper focuses on the study of various existing automated approaches for recognition and extraction of OOI from an image in various scientific and engineering applications. In this study, a categorization is made based on the four principle factors (Input, Object, Feature, Attention) with which each approach is driven. All the approaches discussed in this paper are proved to work efficiently in real environment.
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Anouncia, S. M., & Joseph, J. G. (2009). Approaches for automated object recognition and extraction from images - A study. Journal of Computing and Information Technology, 17(4), 359–370. https://doi.org/10.2498/cit.1001363
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