Paper Title :Contributing Saliency Maps and Visual Features Using RGB-D Images Applied in Industrial Robots

Author :Mahdi Amirsardari, Vahdi Rostami

Article Citation :Mahdi Amirsardari ,Vahdi Rostami , (2024 ) " Contributing Saliency Maps and Visual Features Using RGB-D Images Applied in Industrial Robots " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 80-85, Volume-12,Issue-1

Abstract : Object detection plays a pivotal role in the field of industrial robotics, where precision and adaptability are paramount. However, a major challenge arises when objects with color attributes similar to their environment that often causes less accuracy recognition. This study explores a novel approach, applied in AtWork and industrial robots, to enhance object detection capabilities. This paper introduces an RGB-D imaging approach contributed with saliency detection to bridge the gap between depth-rich information and color-rich representations. The main objective is to extend object recognition beyond shape and size, incorporating nuanced color-based discrimination, a challenge for traditional RGB-based detection. The experimental results have been done on two image datasets. The result 89% accuracy on these datasets show that the contribution of depth and RBG can improve the accuracy of image recognition.

Type : Research paper

Published : Volume-12,Issue-1

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