Publication: YOLOv7 algorithm implementation and image analysis for barcode detection
No Thumbnail Available
Date
2024-07
Authors
Salahuddin bin Nor Azman
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
The implementation of barcode technology has revolutionized manufacturing processes by enhancing supply chain management, boosting productivity, and minimizing errors. Barcode localization and decoding represents a cutting-edge skill, aiming to develop a rapid and precise method of barcode reading. Dynamsoft Barcode Reader (DBR) is a barcode reader equipped algorithms that deliver unmatched speed, accuracy, and read rates in barcode
decoding. However, challenging conditions such as excessive light exposure, low contrast, or poor illumination in the industrial environment can pose difficulties for DBR. To address this, deep learning techniques can be employed for barcode detection, thereby improving detection accuracy. Instead of analysing the entire image, which may contain multiple barcodes, a deep learning model can be trained to detect and crop individual barcodes into a single image, which can then be fed into DBR Python API for decoding. Through the project, it is found that the YOLO model had achieved an average precision and recall of 99.5% and 99.8% respectively. Model deployment was done using new dataset directly from intended use case for the model integration and it is shown that the model achieved a success detection rate of 86.5%. Struggling to detect and misdetection were revealed and it is discussed that background clutter contributes to it. For DBR decoding, two methods are used, which are DBR Online Demo SDK and DBR Python API and achieved a decoding accuracy of 100% and 98.9% for Set 1 and Set 2 images respectively. OpenCV Image Analysis proved that contrast and edge clarity are two perimeters that highly affect DBR capability to decode. As a conclusion, the implementation of YOLOv7-tiny with DBR Python API has resulted in a significant improvement. Thus, the thesis has successfully met its objectives.