Spotting of a Particular Printed Word in Farsi Handwritten Forms Using Deep Learning

Keyword spotting in documents plays a crucial role in information retrieval and document analysis. Recent years have witnessed significant progress in keyword spotting through deep learning methods. This paper introduces a method that utilizes a pre-trained Mask R-CNN with transfer learning to spot the printed keyword in the printed forms filled in handwriting. To address data scarcity and enhance the network's performance, data augmentation methods are employed. Additionally, specific to the keyword , adjustments such as changes in the dimensions and aspect ratio of anchors, are implemented in the region proposal network (RPN). The results illustrate that the proposed method achieves a mean Average Precision (mAP) of 98.1 percent.