| dc.contributor.author | Mohamed Rizon | |
| dc.contributor.author | Haniza, Yazid | |
| dc.contributor.author | Puteh, Saad | |
| dc.contributor.author | Ali Yeon, Md Shakaff, Prof. Dr. | |
| dc.contributor.author | Abdul Rahman, Saad | |
| dc.contributor.author | Mohd Rozailan, Mamat | |
| dc.contributor.author | Sazali, Yaacob, Prof. Dr. | |
| dc.contributor.author | Hazri, Desa, Dr. | |
| dc.contributor.author | Karthigayan, M. | |
| dc.date.accessioned | 2011-03-22T01:48:27Z | |
| dc.date.available | 2011-03-22T01:48:27Z | |
| dc.date.issued | 2006 | |
| dc.identifier.citation | American Journal of Applied Sciences, vol. 3(6), 2006, pages 1876-1878 | en_US |
| dc.identifier.issn | 1546-9239 | |
| dc.identifier.uri | http://www.scipub.org/fulltext/ajas/ajas361876-1878.pdf | |
| dc.identifier.uri | http://dspace.unimap.edu.my/123456789/11348 | |
| dc.description | Link to publisher's homepage at http://www.scipub.org/ | en_US |
| dc.description.abstract | Geometric moment invariant produces a set of feature vectors that are invariant under shifting, scaling and rotation. The technique is widely used to extract the global features for pattern recognition due to its discrimination power and robustness. In this paper, moment invariant is used to identify the object from the captured image using the first invariant (Ø1). The recognition rate for this technique is 90% after the image undergoes suitable processing and segmentation process. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Science Publications | en_US |
| dc.subject | Geometric invariant moment | en_US |
| dc.subject | Object detection | en_US |
| dc.subject | Geometric Moment (GM) | en_US |
| dc.title | Object detection using geometric invariant moment | en_US |
| dc.type | Article | en_US |
