Research On Key Issues In Copyright Protection Of Cartoon Characters

Nowadays, information technology changes human being’s life a lot. In thisprogress, knowledge-based economy and information technology influence eachother, and make greate advances. Cartoon industry is a typical knowledge-basedindustry, and gains a good opportunity for further developing. All the aspects ofcartoon industry, including the producing, broadcasting and consuming, benefit fromthe information technology and make a great progress. However, the informationtechnology also brings more complex copyright problems at the same time, whichmake the cartoon copyright protection an urgent problem.The key issues of the copyright infringement problem in cartoon mainly lie onunauthorized browsing, sharing and copy during the cartoon broadcasting, spreadingand the application. Traditional copyright protection techniques, such aswatermarking and cryptography, are not sufficient for such complex problems.Obviously, cartoon characters are the key content of the cartoon media, which isalso the mostly frequently infringed part. Most of the infringements involve thecartoon characters, so the characters are the invariant theme in the infringements.Therefore, cartoon character protection is the key of the cartoon media copyrightprotection.This thesis focuses on the copyright protection of cartoon media. Firstly, thespecialty of the cartoon image is discussed, and a basic viewpoint is proposed: shapeis the essential element to present the cartoon character and the similarity in shape isthe internal connection between same characters in different images. Secondly, edgeand curve detection methods are proposed to extract the shape in either natural andcartoon images. Then, a new local invariant shape feature is proposed to describethe cartoon characters in the image, in which the location, angle and scale ofcharacter are unknown. Based on this feature, the research on the cartoon characterindexing, detection and selective encryption are done.The main contribution and innovation of this dissertation are described asfollows:Firstly, the learning based edge detection methods for natural images arediscussed and then a new edge detection method based on Fuzzy Weighed SupportVector Machine for Regression is proposed to alleviate the label impression problemand noise. A fuzzy membership is applied to re-weigh the training sample accordingto the distance to the human labels, so that the samples with different reliability aretreated differently to alleviate the label imprecision problem. Then a curveextraction method for cartoon images is proposed to extract the shape in the cartoon image. The two types of curve in the cartoon image are defined and extractedseparately based on their different response to the first and the second orderdirectional derivative. The proposed method is more efficient and produces betterresults.Secondly, a scale and rotation invariant local feature is proposed to describe thelocal shape, and used in the cartoon character retrieval in both the natural image andthe cartoon image. The feature locates at the scale invariant corner and use the shapecontext to describe the shape near the corner, and a feature matching method is usedto compute the similarity between the query and the image in the database. The usedof shape feature fill the gap between the appearance differences between naturalimage and cartoon image, and reduce the disturbance from the background.Thirdly, a Hough voting based cartoon character detection method is studied topreventing the unauthorized sharing in the website. The visual shape words areextracted in the pre-segmented cartoon characters and then a Hough voting schemeis used to present the character. And then a posterior probability conditioned on theexistence of visual words is estimated in the Hough voting space. The proposedmethod is effective as the experimental results show.Fourthly, selective encryption method is investigated in order to protect thecartoon from unauthorized copy. The Thin Plain Spline-Robust Point Matchingmethod is employed to localize the cartoon character accurately, and then a streamcipher based on multi-chaotic systems is used to encrypt and decrypt the characterregion. The selective encryption method encrypts the key content of the cartoon andleaves the others as plain for the preview, which can offer better user experiencewhich make cartoon publish more easily.