Abstract
One of the most crucial skills in a person’s daily life is handwriting. When it comes to making scripts for various professions, doctors, on the other hand, have been familiar with their low-quality handwriting for decades. To solve this, we demonstrated a deep learning-based method for detecting drug names from doctor’s prescriptions, which will benefit the public. The drug is first cropped from the image with reduced dimensions and then fed into two alternative architectures, CRNN alone and EAST + CRNN architecture. The cursive handwritten image is then converted to conventional text using these models. After obtaining the texts, the text is calculated using the CTC loss and the outcome is predicted.
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Acknowledgements
The authors are thankful to Amrita Vishwa Vidyapeetham’s Department of Computer Science and Engineering for providing us with the opportunity to work on medical prescriptions handwriting recognition.
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Henry, A., Sujee, R. (2023). Medical Prescription Label Reading Using Computer Vision and Deep Learning. In: Thakur, M., Agnihotri, S., Rajpurohit, B.S., Pant, M., Deep, K., Nagar, A.K. (eds) Soft Computing for Problem Solving. Lecture Notes in Networks and Systems, vol 547. Springer, Singapore. https://doi.org/10.1007/978-981-19-6525-8_9
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DOI: https://doi.org/10.1007/978-981-19-6525-8_9
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