A Complete Logo Detection/Recognition System for Document Images

Abstract

In this paper, a complete logo detection/ recognition system for document images is proposed. In the proposed system, first, a logo detection method is employed to detect a few regions of interest (logo-patches), which likely contain the logo(s), in a document image. The detection method is based on the piece-wise painting algorithm (PPA) and some probability features along with a decision tree. For the logo recognition, a template based recognition approach is proposed to recognize the logo which may present in every detected logo-patch. The proposed logo recognition strategy uses a search space reduction technique to decrease the number of template logo-models needed for the recognition of a logo in a detected logo-patch. The features used for search space reduction are based on the geometric properties of a detected logo-patch. Based on our experimentations on 1290 document images of Tobacco800 dataset, 99.31% of the logos were detected as logo-patches. Among the detected logo-patches 97.90% of logos were fairly recognized. Considering both logo detection and recognition results, 97.22% of the logos in the document images could truly be detected/recognized as the overall performance of the proposed system.