PCA-Based Relevance Feedback in Document Image Retrieval
Research has been devoted in the past few years to relevance feedback as an effective solution to improve performance of information retrieval systems. Relevance feedback refers to an interactive process that helps to improve the retrieval performance. In this paper, the authors propose the use of relevance feedback to improve Document Image Retrieval System (DIRS) performance. This paper compares a variety of strategies for positive and negative feedback. In addition, feature subspace is extracted and updated during the feedback process using a Principal Component Analysis (PCA) technique and based on user's feedback.