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Detecting and Localizing Dents on Vehicle Bodies Using Region-Based Convolutional Neural Network
Detection and localization of the dents on a vehicle body that occurs during manufacturing is critical to achieve the appearance quality of a new vehicle. This study proposes a region-based convolutional neural network (R-CNN) to detect and localize dents for a vehicle body inspection. For a better feature extraction, this study employed a lighting system, which can highlight dents on an image by projecting the Mach bands (bright-dark stripes). The R-CNN was trained using the highlighted imagesdoi:10.3390/app10041250 fatcat:v754jrb4v5aixchvzf3xzscwtq