Name
Abstract | ||
|---|---|---|
Production of high quality wheat has a great importance especially in the solution of nutrition problems. It is necessary to make decomposition for specifying the quality. Here, high quality and unclassified wheat recognition are realized. The most distinctive feature between high quality and poor quality wheat is the shape difference. In this study, Bag of Contour Fragments (BCF) was used as a shape based descriptor. In contrast to general shape descriptors, BCF represents shape by dividing into small parts rather than entire one. These small fragments are then coded and classified by the Support Vector Machine (SVM) according to their histograms. In the study, a performance of % 70 accuracy rate was achieved. |
Year | Venue | Keywords |
|---|---|---|
2017 | Signal Processing and Communications Applications Conference | bag of contour fragments,wheat,unclassified wheat,shape desciptor |
Field | DocType | ISSN |
Computer vision,Histogram,Pattern recognition,Division (mathematics),Computer science,Support vector machine,Distinctive feature,Artificial intelligence | Conference | 2165-0608 |
Citations | PageRank | References |
0 | 0.34 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ahmet Okan Onarcan | 1 | 0 | 0.34 |
| Kemal Özkan | 2 | 11 | 4.28 |
| Murat Olgun | 3 | 0 | 0.34 |