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Multiple objects recognition for industrial robot applications

Kyekyung Kim, Sangseung Kang, Jaehong Kim, Jaeyeon Lee, Joongbae Kim, Jin Ho Kim

Year
2013
Citations
9

Abstract

Vision-based object recognition has been studied intensively because of many application fields, especially, manufacturing process in industrial robot application. But it has been challenged due to illumination effect, diverse material object, atypical shape object, etc. In this paper, multiple object recognition including complex shape object has been proposed. The object is consisted of variable characteristic, which has reflection material surface wrapped by plastic or flexible shape. Object segmentation using back light and pose estimation by maximal axis detection, and object recognition by NN have developed. We have evaluated recognition performance on database of ETRI, which has acquired under various lighting conditions.

Keywords

Computer visionArtificial intelligenceCognitive neuroscience of visual object recognitionObject (grammar)3D single-object recognitionComputer scienceRobotSegmentationProcess (computing)Object detection

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