Identifying the most relevant tablet regions in the image detection of counterfeit medicines

This paper proposes a novel image-based approach to detect counterfeit medicines and identify the most relevant regions of the tablet in the task of classification. Images of medicine tablets undergo an initial pre-processing step which (i) removes the background to find the region of interest, (ii) clusters individual pixels into super-pixels, and (iii) extracts features containing color and texture information. The classification relying on Support Vector Machine (SVM) defines the class the respective image will be inserted into.

Highlights

• A novel image-based approach is proposed to detect counterfeit medicines and identify the most relevant regions of the tablet in the task of classification

• Support vectors generate a heat map indicating tablet regions that contribute the most to the classification purpose

• The framework is validated in two datasets of authentic and counterfeit tablets

• The method outperformed a competing approach from the literature by yielding more robust explanations

The task of identifying the relevant regions of the tablets for counterfeiting detection is performed using the concept of support vectors, generating a heat map that indicates the regions that contribute the most to the classification purpose. Two datasets containing images of authentic and counterfeit tablets of Cialis and Viagra were used to validate our propositions, achieving correct classification rates of 100% on both datasets. Regarding the task of identifying the most relevant regions, our proposition outperformed the traditional LIME (Local Interpretable Model-agnostic Explanations) method by yielding more robust explanations. Continue on image detection of counterfeit medicines

Fábio do Prado Puglia, Michel José Anzanello, Jacob Scharcanski, Juliana de Abreu Fontes, João Batista Gonçalves de Brito, Rafael Scorsatto Ortiz, Kristiane Mariotti,
Identifying the most relevant tablet regions in the image detection of counterfeit medicines,
Journal of Pharmaceutical and Biomedical Analysis, 2021, 114336, ISSN 0731-7085,
https://doi.org/10.1016/j.jpba.2021.114336.