A method of determining tire condition, wherein the tire condition includes a tread depth, the method comprising: collecting multispectral data of a primary area of a tire with a multispectral camera; determining a secondary area of the tire based on the multispectral data, wherein the secondary area is a sub-area of the primary area, and wherein determining the secondary area includes: determining an exceptional region of the primary area that is coated with debris based on the multispectral data of the primary area; and determining the secondary area to not include the exceptional region of the primary area; collecting a plurality of TOF images, wherein the plurality of TOF images are either of the primary area or the secondary area, wherein the TOF images of the primary area include the exceptional region, wherein the TOF images of the secondary area exclude the exceptional region, wherein each of the plurality of TOF images are collected at a respective exposure time of a plurality of exposure times, and wherein the TOF images include a first image at a first exposure time and a second image at a second exposure time, the first exposure time being less than the second exposure time; edge filtering each of the TOF images to determine a plurality of edge maps; and determining the tire condition of the secondary area based on the plurality of edge maps, wherein determining the tire condition of the secondary area includes: determining a tread measure based on the edge maps and the exposure times, which includes determining a plurality of edge counts by counting the edge pixels of each edge map, wherein each edge count corresponding to a respective exposure time, and wherein the edge pixels each correspond to an edge detection by the edge filtering; and comparing the edge count to a reference edge count for each exposure time, wherein the method comprises exclusion filtering each of the plurality of TOF images and/or plurality of edge maps to exclude the exceptional region before determining the tire condition if the plurality of TOF images are of the primary area. collecting multispectral data of a primary area of a tire with a multispectral camera; determining a secondary area of the tire based on the multispectral data, wherein the secondary area is a sub-area of the primary area, and wherein determining the secondary area includes: determining an exceptional region of the primary area that is coated with debris based on the multispectral data of the primary area; and determining the secondary area to not include the exceptional region of the primary area; determining an exceptional region of the primary area that is coated with debris based on the multispectral data of the primary area; and determining the secondary area to not include the exceptional region of the primary area; collecting a plurality of TOF images, wherein the plurality of TOF images are either of the primary area or the secondary area, wherein the TOF images of the primary area include the exceptional region, wherein the TOF images of the secondary area exclude the exceptional region, wherein each of the plurality of TOF images are collected at a respective exposure time of a plurality of exposure times, and wherein the TOF images include a first image at a first exposure time and a second image at a second exposure time, the first exposure time being less than the second exposure time; edge filtering each of the TOF images to determine a plurality of edge maps; and determining the tire condition of the secondary area based on the plurality of edge maps, wherein determining the tire condition of the secondary area includes: determining a tread measure based on the edge maps and the exposure times, which includes determining a plurality of edge counts by counting the edge pixels of each edge map, wherein each edge count corresponding to a respective exposure time, and wherein the edge pixels each correspond to an edge detection by the edge filtering; and comparing the edge count to a reference edge count for each exposure time, wherein the method comprises exclusion filtering each of the plurality of TOF images and/or plurality of edge maps to exclude the exceptional region before determining the tire condition if the plurality of TOF images are of the primary area. determining a tread measure based on the edge maps and the exposure times, which includes determining a plurality of edge counts by counting the edge pixels of each edge map, wherein each edge count corresponding to a respective exposure time, and wherein the edge pixels each correspond to an edge detection by the edge filtering; and comparing the edge count to a reference edge count for each exposure time, wherein the method comprises exclusion filtering each of the plurality of TOF images and/or plurality of edge maps to exclude the exceptional region before determining the tire condition if the plurality of TOF images are of the primary area.