Sorting support apparatus, sorting support system, sorting support method, and program
US-2020393390-A1 · Dec 17, 2020 · US
US12330190B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12330190-B2 |
| Application number | US-202117997368-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 23, 2021 |
| Priority date | Apr 30, 2020 |
| Publication date | Jun 17, 2025 |
| Grant date | Jun 17, 2025 |
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Provided are a scrap determination system and method that can improve scrap determination techniques. A scrap determination system (1) comprises: a first scrap determination model (221) generated using teaching data including first learning images, and determines, based on a camera image, grade of scrap in the image and a ratio of the grade; a second scrap determination model (222) generated using teaching data including second learning images, and determines, based on the image, grade of scrap in the image and a ratio of the grade; a selection model (223) configured to determine which of the first scrap determination model (221) and the second scrap determination model (222) is to be used, based on the image; and an output section (24) configured to output information of each grade of scrap and a ratio of the grade determined based on the image using the model selected by the selection model (223).
Opening claim text (preview).
The invention claimed is: 1. A scrap determination system comprising: an acquisition section configured to acquire a camera image including scrap; a first scrap determination model generated using teaching data including first learning images, and configured to determine, based on the camera image, each of the grade of the scrap included in the camera image and a ratio of the grade; a second scrap determination model generated using teaching data including second learning images different from the first learning images, and configured to determine, based on the camera image, each of the grade of the scrap included in the camera image and a ratio of the grade; a selection model configured to determine which of the first scrap determination model and the second scrap determination model is to be used, based on the camera image; and an output section configured to output information of each grade of the scrap and a ratio of the grade determined based on the camera image using a model selected by the selection model out of the first scrap determination model and the second scrap determination model. 2. The scrap determination system according to claim 1 , wherein the first learning images are each an image of single-grade iron scrap, and when determining each of the grade of the scrap included in the camera image and a ratio of the grade using the first scrap determination model, the ratio of the grade is determined based on an area ratio of scrap of the grade in the camera image. 3. The scrap determination system according to claim 1 , wherein the second learning images are each an image of mixed-grade iron scrap. 4. The scrap determination system according to claim 1 , wherein the first learning images, the second learning images, and the camera image are each normalized based on zoom information corresponding to the camera image. 5. The scrap determination system according to claim 4 , wherein the first learning images, the second learning images, and the camera image are each normalized to a magnification factor that differs depending on the zoom information corresponding to the camera image. 6. The scrap determination system according to claim 1 , wherein at least one of the first scrap determination model, the second scrap determination model, and the selection model is relearned based on the camera image and the information output by the output section. 7. A scrap determination method that uses: a first scrap determination model generated using teaching data including first learning images, and configured to determine, based on a camera image including scrap, each of the grade of the scrap included in the camera image and a ratio of the grade; and a second scrap determination model generated using teaching data including second learning images different from the first learning images, and configured to determine, based on the camera image, each of the grade of the scrap included in the camera image and a ratio of the grade, the scrap determination method comprising: acquiring the camera image; selecting, based on the camera image, which of the first scrap determination model and the second scrap determination model is to be used, by a selection model; and outputting information of each grade of the scrap and a ratio of the grade determined based on the camera image using a model selected by the selection model out of the first scrap determination model and the second scrap determination model. 8. The scrap determination system according to claim 2 , wherein the second learning images are each an image of mixed-grade iron scrap. 9. The scrap determination system according to claim 2 , wherein the first learning images, the second learning images, and the camera image are each normalized based on zoom information corresponding to the camera image. 10. The scrap determination system according to claim 9 , wherein the first learning images, the second learning images, and the camera image are each normalized to a magnification factor that differs depending on the zoom information corresponding to the camera image. 11. The scrap determination system according to claim 2 , wherein at least one of the first scrap determination model, the second scrap determination model, and the selection model is relearned based on the camera image and the information output by the output section.
Sorting of waste or refuse · CPC title
Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming · CPC title
of area, perimeter, diameter or volume · CPC title
Recycling · CPC title
Enabling technologies or technologies with a potential or indirect contribution to greenhouse gas [GHG] emissions mitigation · CPC title
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