Food safety inspection using “from presence to classification” object-detection model

摘要

With multiresolution decomposition and forest representation of wavelet transforms, we implemented a “from presence to classification” object-detection model. Three aspects of this model are studied. First, the presence of an object is quickly detected with fewer data manipulations at the coarsest resolution; secondly, object classification with high accuracy is fulfilled at the full resolution; and thirdly, the propagation in the coarse-to-fine process is studied in terms of coefficient propagation within a coefficient tree. We applied this model to internal deboned poultry inspection. As soon as the presence of a hazardous object was detected at a coarse resolution, a signal was actuated to reject the chicken fillet containing foreign inclusions before packing. Only with small foreign inclusions did we need to resort to finer resolution analysis.