Automatic Pill Identification from Pillbox Images
There is a vital need for fast and accurate recognition of medicinal tablets and capsules. Efforts to date have centered on automatic segmentation, color and shape identification. Our system combines these with preprocessing before imprint recognition. Using the National Library of Medicine Pillbox database, regression analysis applied to automatic color and shape recognition allows for successful pill identification. Measured errors for the subtasks of segmentation and color recognition for this database are 1.9% and 2.2%, respectively. Imprint recognition with optical character recognition (OCR) is key to exact pill ID, but remains a challenging problem, therefore overall recognition accuracy is not yet known.
D. E. Madsen et al., "Automatic Pill Identification from Pillbox Images," Proceedings of the 8th International Conference on Computer Vision Theory and Applications (2013, Barcelona, Spain), vol. 1, pp. 378 - 384, SciTePress, Feb 2013.
The definitive version is available at https://doi.org/10.5220/0004303603780384
8th International Conference on Computer Vision Theory and Applications (2013: Feb. 21-24, Barcelona, Spain)
Electrical and Computer Engineering
Keywords and Phrases
Automatic Segmentations; Color Clustering; Color Space; National Library Of Medicines; Optical Character Recognition (OCR); Recognition Accuracy; Shape Identifications; Shape Recognition; Image Analysis; Image Segmentation; Regression Analysis; Color; Segmentation
International Standard Book Number (ISBN)
Article - Conference proceedings
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01 Feb 2013