Name
Title | ||
|---|---|---|
Combined Use Of Fcn And Harris Corner Detection For Counting Wheat Ears In Field Conditions |
Abstract | ||
|---|---|---|
Accurate counting of wheat ears in field conditions is vital to predict yield and for crop breeding. To quickly and accurately obtain the number of wheat ears in a field, we propose herein a method to count wheat ears based on fully convolutional network (FCN) and Harris corner detection. The technical procedure consists essentially of 1) constructing a dataset of wheat-ear images from acquired red-green-blue (RGB) images; 2) training a FCN as the wheat-ear segmentation model by using the constructed image dataset; 3) preparing testing images and inputting them into the segmentation model to get the initial segmentation results; 4) binarizing the initial segmentation by using the Otsu algorithm (to facilitate subsequent processing); and 5) applying Harris corner detection after extracting the wheat-ear skeleton to obtain the number of wheat ears in the images. The segmentation results show that the proposed FCN-based segmentation model segments wheat ears with an average accuracy of 0.984 and at low computational cost. An average of only 0.033 s is required to segment a 256x256-pixel wheat-ear image. Moreover, the segmentation result is improved by nearly 10% compared with the previous segmentation methods under conditions of wheat-ear occlusion, leaf occlusion, uneven illumination, and soil disturbance. Subsequently, the proposed counting method achieves good results, with an average accuracy of 0.974, a coefficient of determination (R-2) of 0.983, and a root mean square error (RMSE) of 14.043. These metrics are all improved by 10% compared with the previous methods. These results show that the proposed method accurately counts wheat ears even under conditions of wheat-ear adhesion. Furthermore, the results provide an important technique for studying wheat phenotyping. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ACCESS.2019.2958831 | IEEE ACCESS |
Keywords | DocType | Volume |
Wheat-ear counting, fully convolutional network, wheat-ear adhesion, Harris corner detection, field conditions | Journal | 7 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daoyong Wang | 1 | 0 | 0.68 |
| Yuanyuan Fu | 2 | 0 | 0.34 |
| Gui-Jun Yang | 3 | 148 | 33.61 |
| Xiaodong Yang | 4 | 58 | 17.09 |
| Liang Dong | 5 | 326 | 52.32 |
| Chengquan Zhou | 6 | 0 | 0.34 |
| Ning Zhang | 7 | 0 | 0.34 |
| Hongya Wu | 8 | 0 | 0.34 |
| Dongyan Zhang | 9 | 1 | 2.38 |