TY  - JOUR
AU  - Cha, KyeongMin
AU  - Woo, Hyun-Ki
AU  - Park, Dohyun
AU  - Chang, Dong Kyung
AU  - Kang, Mira
PY  - 2021
DA  - 2021/7/28
TI  - Effects of Background Colors, Flashes, and Exposure Values on the Accuracy of a Smartphone-Based Pill Recognition System Using a Deep Convolutional Neural Network: Deep Learning and Experimental Approach
JO  - JMIR Med Inform
SP  - e26000
VL  - 9
IS  - 7
KW  - pill recognition
KW  - deep neural network
KW  - image processing
KW  - color space
KW  - color difference
KW  - pharmaceutical
KW  - imaging
KW  - photography
KW  - neural network
KW  - mobile phone
AB  - Background: Pill image recognition systems are difficult to develop due to differences in pill color, which are influenced by external factors such as the illumination from and the presence of a flash. Objective: In this study, the differences in color between reference images and real-world images were measured to determine the accuracy of a pill recognition system under 12 real-world conditions (ie, different background colors, the presence and absence of a flash, and different exposure values [EVs]). Methods: We analyzed 19 medications with different features (ie, different colors, shapes, and dosages). The average color difference was calculated based on the color distance between a reference image and a real-world image. Results: For images with black backgrounds, as the EV decreased, the top-1 and top-5 accuracies increased independently of the presence of a flash. The top-5 accuracy for images with black backgrounds increased from 26.8% to 72.6% when the flash was on and increased from 29.5% to 76.8% when the flash was off as the EV decreased. However, the top-5 accuracy increased from 62.1% to 78.4% for images with white backgrounds when the flash was on. The best top-1 accuracy was 51.1% (white background; flash on; EV of +2.0). The best top-5 accuracy was 78.4% (white background; flash on; EV of 0). Conclusions: The accuracy generally increased as the color difference decreased, except for images with black backgrounds and an EV of −2.0. This study revealed that background colors, the presence of a flash, and EVs in real-world conditions are important factors that affect the performance of a pill recognition model. 
SN  - 2291-9694
UR  - https://medinform.jmir.org/2021/7/e26000
UR  - https://doi.org/10.2196/26000
UR  - http://www.ncbi.nlm.nih.gov/pubmed/34319239
DO  - 10.2196/26000
ID  - info:doi/10.2196/26000
ER  -