Hybrid Classification of Resistors through Image Processing

Digital image processing consists of a set of techniques for contrast enhancement, noise reduction, image sharpening, segmentation, object recognition, and quantitative analysis of the image. In this work, we focus on object recognition on images containing electronic resistors. Our system classifies those resistors according to the colored bands of the resistors found in the image. This paper will introduce the system, presenting an architecture that leads to a high performance image processing system and describing a hybrid programming model, through the combined operation of processes and threads to meet the requirements of that system. In addition, the paper presents some discussion about the performance on different resources configuration on a cluster of multi-core nodes.