TMT(Thermo Mechanical treatment) rods are the walloping production of the steel industries and they require tailor-made measurements for each construction site. for that there are huge machines that will make the task of cutting TMT rods easier for industries. while cutting the rods they measure for efficient cutting for that they use a photoelectric sensor, Manual labor, and complex computing machine that ended up in huge maintenance of the machines and time-consuming process, in the last decade research on Digital image processing and computer vision has seen much progress. I developed a methodology that is adaptable for the industries in measuring TMT rods much more efficiently , robust towards cram-full of rods, and minimizing the error rate. The captured digital image first undergoes the preprocessing phase where the first step is image enhancement and then edge detection, which extracts the TMT rods edges then followed by the diameter calculations (pixels per metric). An experiment was conducted on a variety of challenging conditions to demonstrate the capability of our approach to a good measure of success This concept gives me optimism for the future of AI (Computer Vision) in construction equipment and materials. The challenges became even greater when it came to the production level, as construction sites were littered with sawdust, which caused a lot of noise in the image and made our job even more difficult in the preprocessing stage. Another issue was the lack of a bright light, which we needed to capture the image. A right contrast of light is required while capturing the image that will help us in identifying the edges of the rod this was later rectified through a contrast library mdoule
TMT(Thermo Mechanical treatment) rods are the walloping production of the steel industries and they require tailor-made measurements for each construction site. for that there are huge machines that will make the task of cutting TMT rods easier for industries. while cutting the rods they measure for efficient cutting for that they use a photoelectric sensor, Manual labor, and complex computing machine that ended up in huge maintenance of the machines and time-consuming process, in the last decade research on Digital image processing and computer vision has seen much progress. I developed a methodology that is adaptable for the industries in measuring TMT rods much more efficiently , robust towards cram-full of rods, and minimizing the error rate. The captured digital image first undergoes the preprocessing phase where the first step is image enhancement and then edge detection, which extracts the TMT rods edges then followed by the diameter calculations (pixels per metric). An experiment was conducted on a variety of challenging conditions to demonstrate the capability of our approach to a good measure of success This concept gives me optimism for the future of AI (Computer Vision) in construction equipment and materials. The challenges became even greater when it came to the production level, as construction sites were littered with sawdust, which caused a lot of noise in the image and made our job even more difficult in the preprocessing stage. Another issue was the lack of a bright light, which we needed to capture the image. A right contrast of light is required while capturing the image that will help us in identifying the edges of the rod this was later rectified through a contrast library mdoule
