Manufacturing Defects Visualization via Robust Edge-Based Registration

Atsunori Moteki, Nobuyasu Yamaguchi, Ayu Karasudani, Yoshie Kobayashi, Toshiyuki Yoshitake, Junya Kato, Tomohiro Aoyagi

Abstract: We propose a visualization method for inspecting manufacturing defects. Industrial products have many straight lines and little texture; therefore, the proposed method uses edges for estimating 6DoF pose of the products (registration). To prevent combinatorial explosion, our method reduces the number of combinations by the condition of edges' geometrical distribution. Moreover, manufacturing defects are detected and visualized by robust registration based on the LMedS. This method realizes on-site product inspection for unskilled workers unfamiliar with AR, and decreases the cost of re-manufacturing. We evaluate our method quantitatively using original CG and real image dataset.