A Survey on Change Detection Techniques in Document Images
Abhinandan Kumar Pun Mohammed Javed David S. Doermann
The problem of change detection in images finds application in different
domains like diagnosis of diseases in the medical field, detecting growth
patterns of cities through remote sensing, and finding changes in legal
documents and contracts. However, this paper presents a survey on core
techniques and rules to detect changes in different versions of a document
image. Our discussions on change detection focus on two categories --
content-based and layout-based. The content-based techniques intelligently
extract and analyze the image contents (text or non-text) to show the possible
differences, whereas the layout-based techniques use structural information to
predict document changes. We also summarize the existing datasets and
evaluation metrics used in change detection experiments. The shortcomings and
challenges the existing methods face are reported, along with some pointers for
future research work.