Segmentation strategies with multiple analysis for an SMD object recognition system

We present two segmentation strategies that use multiple analysis for the preprocessing stage of an object recognition system to detect the presence of surface mounted devices (SMD) on printed circuit boards. This work concentrates only on the preprocessing stage and simple segmentation algorithms for fast real-time implementation. The system uses two images of the same scene, with top and side illuminations. One approach uses both the top- and the side-illuminated images while the other one uses only the top-illuminated image. Experiments are performed using the two model-based segmentation approaches, which produce a gray level region of interest (ROI) that has the SMD isolated as a target when it is present or a smaller area when the SMD is absent. The suppression of the copper-pads is a key step in the processing. For the first strategy, the comparison criteria used to evaluate its performance are the binary area and the energy of the ROI. For the second strategy, our evaluation is a comparison of the results with a fixed size reference ROI mask located at a centroid chosen by visual analysis of the image. Using a database of 1500 images, the distributions of the two comparison criteria are shown for three possible scenes: the SMD is present in the images, the SMD is absent but a speck of glue is present, or the SMD and the glue are both absent. Examples of the processing results are shown