As a core component of reusable thermal protection systems for spacecraft, ceramic fiber heat shields rely on the integrity of their borosilicate glass coatings to determine aerodynamic performance and operational safety. However, traditional 3D point cloud detection methods face challenges in defect localization and measurement due to the high similarity between complex surface textures and actual defect morphologies during inspection. To address these issues, this study proposes a two-stage measurement protocol. This method first performs 2D defect localization. Initial candidate area screening using relaxed threshold values on depth maps, followed by relative slope feature extraction to refine detection and eliminate texture interference; it then conducts 3D local measurement. Mapping localized defect regions to 3D point clouds and applying RANSAC/DBSCAN algorithms for precise dimensional analysis. Experimental results demonstrate significant improvements: compared to edge detection methods, the proposed approach achieves 83.3% defect detection accuracy (from 50% baseline) with the false positive rate reduced to 33.33%. When compared to global RANSAC/DBSCAN methods, it improves detection rate from 50% to 83.3% while reducing false positives from 50% to 33.33%, with detection capability extending to minimum 30 μm depth defects. The framework′s superior localization performance under complex texture interference is conclusively validated.