an improved fingerprint-based document image retrieval using multi-resolution histogram of oriented gradient features

Recently most of the documents are authenticated by using a latent fingerprint impression. examples of such documents are property registration, banking transactions, insurance documents, etc. the fingerprint-based document retrieval (fpdir) has emerged to provide an easier way of accessing, browsing, or searching such document images. this paper proposes efficient fingerprint-based document image retrieval by employing multi-resolution histogram of oriented gradient (hog) features. the preprocessing technique presented in this paper employs a combination of top-hat and bottom-hat filtering operations to enhance the detected fingerprint image. multi-resolution hog features are constructed from horizontal, vertical and diagonal directional components of the enhanced fingerprint image. finally, a standardized euclidean distance metric is used as a tool for matching, ranking and retrieval of the document images. the proposed system is assessed by experimenting with a dataset of 1200 images. the precision and recall results obtained using the proposed research work have given an improvement of 8% to 14% in retrieval performance compared to earlier methods.