Name
Abstract | ||
|---|---|---|
In allusion to the present heterotrophic bacteria colony counting method having the disadvantages of subjectivity, big error and low efficiency, we proposed a recognition method for heterotrophic bacteria colony based on SVM. After a series of pre-processing and segmentation to the acquired colony image, 6 feature parameters such as: area, perimeter, equivalent diameters of colony individual and non-colony ones were extracted. Then we adopted SVM to recognize them and the recognition rate of 98.7% was obtained. This means the effectiveness of the feature extraction method and the feasibility of support vector machines used for heterotrophic bacteria colony recognition. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CSSE.2008.485 | CSSE (1) |
Keywords | Field | DocType |
big error,support vector machine,colony individual,feature parameter,recognition method,heterotrophic bacteria colony,recognition rate,feature extraction method,present heterotrophic bacteria colony,heterotrophic bacteria colony recognition,acquired colony image,feature extraction,pixel,kernel,support vector machines,pattern recognition,microorganisms,shape | Kernel (linear algebra),Colony counting,Pattern recognition,Computer science,Segmentation,Support vector machine,Feature extraction,Artificial intelligence,Bacteria,Machine learning | Conference |
Citations | PageRank | References |
1 | 0.36 | 1 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Men | 1 | 5 | 3.86 |
| Yujie Wu | 2 | 12 | 1.89 |
| Yanchun Gao | 3 | 1 | 0.70 |
| Zhen Kou | 4 | 1 | 0.36 |
| Zhiming Xu | 5 | 82 | 18.81 |
| Shanrang Yang | 6 | 2 | 1.41 |