A system for determining a wear condition for a belt adapted for use with machinery, the system comprising: an image-capture device configured to capture a first image (Fig.7A) of the belt, the first image (Fig.7A) comprising a greyscale or a color image that includes image data for a top and bottom edge (616, 620) of the belt and at least one marked feature (608a-N) between the top and bottom edge (616, 620) of the belt; an image conversion module configured to receive the first image (Fig.7A) of the belt and convert the first image (Fig.7A) into a second image (Fig.7B), wherein the second image (Fig.7B) comprises a black-and-white image, wherein the image conversion module converts the first image (Fig.7A) into the second image (Fig.7B) by determining a contrast threshold value that is applied to pixels in the first image (Fig.7A), wherein pixels in the first image (Fig.7A) having a pixel value that is less than or equal to the contrast threshold value are assigned a first binary pixel value in the second image (Fig.7B) and wherein pixels in the first image having a pixel value that is greater than the contrast threshold value are assigned a second binary pixel value in the second image (Fig.7B), and wherein the contrast threshold value is determined by analyzing the first image (Fig.7A) with a plurality of different candidate threshold values, correlating each of the candidate threshold values to a determined rib count, identifying a most-frequently occurring rib count from the plurality of different candidate threshold values, and determining the contrast threshold value as an average threshold value from threshold values that have been correlated to the most-frequently occurring rib count; an analysis module configured to analyze the second image (Fig.7B) and detect contours of at least one marked feature, and the topmost and bottommost edge of the belt therein, wherein the analysis module is further configured to convert pixels into physical dimensions and based on such conversions determine a physical size of the at least one marked feature (608a-N) and a physical distance between the at least one marked feature (608a-N) and one or both of the top and bottom (616, 620) of the belt, and wherein the analysis module is further configured to determine a wear condition for the belt based on the determined physical distance between the at least one marked feature (608a-N) and one or both of the top and bottom (616, 620) of the belt; and a reporting module configured to generate and transmit a report to a user that includes the determined wear condition for the belt. an image-capture device configured to capture a first image (Fig.7A) of the belt, the first image (Fig.7A) comprising a greyscale or a color image that includes image data for a top and bottom edge (616, 620) of the belt and at least one marked feature (608a-N) between the top and bottom edge (616, 620) of the belt; an image conversion module configured to receive the first image (Fig.7A) of the belt and convert the first image (Fig.7A) into a second image (Fig.7B), wherein the second image (Fig.7B) comprises a black-and-white image, wherein the image conversion module converts the first image (Fig.7A) into the second image (Fig.7B) by determining a contrast threshold value that is applied to pixels in the first image (Fig.7A), wherein pixels in the first image (Fig.7A) having a pixel value that is less than or equal to the contrast threshold value are assigned a first binary pixel value in the second image (Fig.7B) and wherein pixels in the first image having a pixel value that is greater than the contrast threshold value are assigned a second binary pixel value in the second image (Fig.7B), and wherein the contrast threshold value is determined by analyzing the first image (Fig.7A) with a plurality of different candidate threshold values, correlating each of the candidate threshold values to a determined rib count, identifying a most-frequently occurring rib count from the plurality of different candidate threshold values, and determining the contrast threshold value as an average threshold value from threshold values that have been correlated to the most-frequently occurring rib count; an analysis module configured to analyze the second image (Fig.7B) and detect contours of at least one marked feature, and the topmost and bottommost edge of the belt therein, wherein the analysis module is further configured to convert pixels into physical dimensions and based on such conversions determine a physical size of the at least one marked feature (608a-N) and a physical distance between the at least one marked feature (608a-N) and one or both of the top and bottom (616, 620) of the belt, and wherein the analysis module is further configured to determine a wear condition for the belt based on the determined physical distance between the at least one marked feature (608a-N) and one or both of the top and bottom (616, 620) of the belt; and a reporting module configured to generate and transmit a report to a user that includes the determined wear condition for the belt.