1.0Finding Dents and Dings With a Drone using Structured Lighthttps://mscvprojects.ri.cmu.edu/2025team5rich600338<blockquote class="wp-embedded-content" data-secret="c8mOFfWQlh"><a href="https://mscvprojects.ri.cmu.edu/2025team5/method/">Method</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://mscvprojects.ri.cmu.edu/2025team5/method/embed/#?secret=c8mOFfWQlh" width="600" height="338" title="“Method” — Finding Dents and Dings With a Drone using Structured Light" data-secret="c8mOFfWQlh" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! This file is auto-generated */ !function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document); //# sourceURL=https://mscvprojects.ri.cmu.edu/2025team5/wp-includes/js/wp-embed.min.js </script> Pipeline We propose a two stage detection system for identifying surface deformities such as dents and dings. The first stage uses structured light scanning to capture detailed geometric data and detect deviations from the expected surface profile. In the second stage, a machine learning classification pipeline filters out false positives such as screws, rivets, and … Continue reading ""https://mscvprojects.ri.cmu.edu/2025team5/wp-content/uploads/sites/132/2025/12/Pipeline_full_updated-1.png23281645