*3.1. Image Acquisition and Classification*

*3.1. Image Acquisition and Classification*  The experimental dataset covers 12 representative images which consist of four empty belt images labelled as one, four mixed material images labelled as two, and four coarse material images labelled as zero. All images were taken from the PCS system at different times. We selected four empty belt images including an empty belt with water stains, an empty belt with small particles, an image taken by a telephoto lens, and an image taken by a short focal length lens. The features of coarse material images are obvious and similar. The four coarse material images were selected randomly. The four mixed material images were selected consisting of 100%, 90%, 70%, and 50% fine material. The raw images were divided into the following four groups: one empty belt image, one mixed material image, and one coarse material image in each group. In order to compare the segmentation results of the different algorithms, the designated region of raw images was processed by using different algorithms. The size of the designated region was 1202 × 631 (JPEG file). Manual segmentation was used to obtain accurate segmentation images. Images from group one (as shown in Figure 9a) were processed using PCS, CIS, and FIS, respectively, for evaluating each algorithm. The experimental dataset covers 12 representative images which consist of four empty belt images labelled as one, four mixed material images labelled as two, and four coarse material images labelled as zero. All images were taken from the PCS system at different times. We selected four empty belt images including an empty belt with water stains, an empty belt with small particles, an image taken by a telephoto lens, and an image taken by a short focal length lens. The features of coarse material images are obvious and similar. The four coarse material images were selected randomly. The four mixed material images were selected consisting of 100%, 90%, 70%, and 50% fine material. The raw images were divided into the following four groups: one empty belt image, one mixed material image, and one coarse material image in each group. In order to compare the segmentation results of the different algorithms, the designated region of raw images was processed by using different algorithms. The size of the designated region was 1202 × 631 (JPEG file). Manual segmentation was used to obtain accurate segmentation images. Images from group one (as shown in Figure 9a) were processed using PCS, CIS, and FIS, respectively, for evaluating each algorithm. Other images were processed and evaluated by using our method.

Other images were processed and evaluated by using our method.

*Minerals* **2020**, *10*, 1115 9 of 16

**Figure 9.** The segmentation results processed by different algorithms: the original images (**a**), manual segmentation (**b**), process control system (PCS) (**c**), CIS (**d**), and FIS (**e**). **Figure 9.** The segmentation results processed by different algorithms: the original images (**a**), manual segmentation (**b**), process control system (PCS) (**c**), CIS (**d**), and FIS (**e**).
