Biblio

Trademarks are recognizable images and/or words used to distinguish various products or services. They become associated with the reputation, innovation, quality, and warranty of the products. Countries around the world have offices for industrial/intellectual property (IP) registration. A new trademark image in application for registration should be distinct from all the registered trademarks. Due to the volume of trademark registration applications and the size of the databases containing existing trademarks, it is impossible for humans to make all the comparisons visually. Therefore, technological tools are essential for this task. In this work we use a pre-trained, publicly available Convolutional Neural Network (CNN) VGG19 that was trained on the ImageNet database. We adapted the VGG19 for the trademark image retrieval (TIR) task by fine tuning the network using two different databases. The VGG19v was trained with a database organized with trademark images using visual similarities, and the VGG19c was trained using trademarks organized by using conceptual similarities. The database for the VGG19v was built using trademarks downloaded from the WEB, and organized by visual similarity according to experts from the IP office. The database for the VGG19c was built using trademark images from the United States Patent and Trademarks Office and organized according to the Vienna conceptual protocol. The TIR was assessed using the normalized average rank for a test set from the METU database that has 922,926 trademark images. We computed the normalized average ranks for VGG19v, VGG19c, and for a combination of both networks. Our method achieved significantly better results on the METU database than those published previously.

A trademark may be a word, phrase, symbol, sound, color, scent or design, or combination of these, that identifies and distinguishes the products or services of a particular source from those of others. Obtaining a trademark is a complex, time intensive and costly process that involves varied steps before the trademark can be registered including searching prior trademarks, filing of the trademark application, review of the trademark application and final publication for opposition by the public. Currently, the process of trademark registration, renewal and validation faces numerous challenges such as the requirement for registration in different jurisdictions, maintenance of centralized databases in different jurisdictions, proving the authenticity of the physical trademark documents, identifying the violation and abuse of the intellectual property etc. to name a few. Recently, blockchain technology has shown great potential in a variety of industries such as finance, education, energy and resource management, healthcare, due to its decentralization and non-tampering features. Furthermore, in the recent years, smart contracts have attracted increased attention due to the popularity of blockchains. In this study, we have utilized Hyperledger fabric as the permissioned blockchain framework along with smart contracts to provide solution to the financial, procedural, enforcement and protection related challenges of the current trademark system. Our blockchain based application seeks to provide a secure, decentralized, immutable trademark system that can be utilized by the intellectual property organizations across different jurisdictions for easily and effectively registering, renewing, validating and distributing digital trademark certificates.