Detection of Punjabi Newspaper Articles Using a Deep Learning Approach

For many years, newspapers have been excellent providers of information. To extract meaningful information, it is imperative to digitize these newspapers. In the case of Punjabi newspapers, the same is necessary. In this study, we used newspaper image segmentation to separate the various articles from the Punjabi newspapers. Different barriers in the extraction of Punjabi newspapers are discussed. Also, we have assembled a dataset of 400 newspaper images, and these images have been trained using cutting-edge object detection models Faster RCNN. The experimental results show that these models for extracting articles produced good outcomes with average accuracy of 81.8% for all classes.