Partial Copy Detection for Copyright Protection of Line Drawings

Abstract

Line drawings are a type of images that consist of distinct straight and curved lines. Such as graphs and comics, line drawings are an important part of image publications, which have requirements of copyright protection. In practice, illegal users not only use the whole image directly, but also copy some parts from the original ones, which are called partial copies. In that case, partial copies can be embedded into other images. In addition, various kinds of image transformations can also be applied. Especially, in the case of line drawings, handwriting can be applied as a method of producing illegal copies, which are more difficult to be detected. To solve this problem, we apply image retrieval using local feature matching to detect illegal copies. Specifically, we propose to apply MSER as a region detector and HOG as a feature descriptor, and compress the dimensions of local feature vectors by using PCA to reduce the database size and detection time. From experimental results, we show the effectiveness of the proposed method for detecting not only printed partial copies but also handwritten ones from complex backgrounds.

Note