| dc.contributor.author | Soni, Pratima | |
| dc.description.abstract | A Content-Based Image Retrieval (CBIR) system can help in detecting trademark infringement. This paper describes an improvement and extension of previous work for the existing Universal Model for a CBIR system, which only uses texture along with color to produce a reliable and capable system. To enhance the security and efficiency of the CBIR based Universal Model, the extension is a Multi Feature CBIR Model that can utilize many parameters including color, texture, and shape with the facility of choosing a suitable and flexible set of features. The supported selection techniques give priority to individual features and help increase the efficiency of the system. I am going to provide write-ups with the proven computational work over the existing feature methods of the Universal Model, which becomes the foundation for the Multi-Feature CBIR Model. In comparison to the Universal Model, the Multi-Feature CBIR Model can obtain higher recall and precision values. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Multi Feature CBIR Model for Trademark Image Distinctiveness | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2019-05-20T21:25:54Z | |
| dc.date.available | 2019-05-20T21:25:54Z | |
| dc.date.issued | 2019 | en_US |
| dc.identifier.uri | https://hdl.handle.net/10365/29757 | |
| dc.subject.lcsh | Content-based image retrieval. | |
| dc.subject.lcsh | Image analysis. | |
| dc.subject.lcsh | Image processing -- Digital techniques. | |
| dc.subject.lcsh | Multimedia systems. | |
| dc.subject.lcsh | Trademark infringement -- Prevention. | |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Engineering | en_US |
| ndsu.department | Computer Science | en_US |
| ndsu.program | Software Engineering | en_US |
| ndsu.advisor | Nygard, Kendall | |
