Machine assisted visual grading of rare collectibles over the Internet

Accurately identifying, grading and then determining the authenticity of rare collectible items such as coins, stamps, cards, comic books and artwork is a subjective non-automated process conducted by appraisers or graders. Appraisers and graders are usually human experts in their respective fields that draw on large established pools of domain knowledge, opinions of other experts in their field and make comprehensive comparisons to other ‘works ’ in the field to assist them in arriving at their findings. As with many professions the credentials for a person establishing himself or herself as ‘an expert ’ can range from being non-existent to possessing a long list of impressive industry certifications. This study examines the human visual recognition process in the grading of rare collectibles and addresses a number of issues, limitations and constraints inherent to human visual recognition as a way of explaining grading variation. The study is then extended by the development of a machine-based system that removes the subjective human characteristics when grading, and is capable of grading rare collectibles by producing consistent and repeatable results. Finally, a machine-assisted human recognition system is developed that combines the technical and subjective attributes of human and machine grading. The purpose of this research is to determine whether humans, machine systems, or hybrid human-machine systems are better at determining the condition, or grade, of collectible items from digital images over the Internet. The strengths and limitations of both human and machine based grading are studied and explored in a theoretical framework. The capabilities of humans and machine are being examined to explain why previous attempts at computer based grading were unsuccessful and to document why humans grade collectibles in an inconsistent fashion