HSV Color-Space-Based Automated Object Localization for Robot Grasping without Prior Knowledge
| Autor: | Heechul Bae, Hyonyoung Han, Min-Gi Kim, Young-Kuk Kim, Hyun-Chul Kang, Ji-Yeon Son |
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| Rok vydání: | 2021 |
| Předmět: |
Technology
Similarity (geometry) QH301-705.5 Computer science Machine vision QC1-999 ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION HSL and HSV HSV color space General Materials Science Computer vision Biology (General) teaching-less robot QD1-999 Instrumentation Fluid Flow and Transfer Processes business.industry Physics Process Chemistry and Technology smart factory General Engineering Engineering (General). Civil engineering (General) Object (computer science) Automation Computer Science Applications Chemistry Robot Artificial intelligence Noise (video) TA1-2040 business Reset (computing) object localization |
| Zdroj: | Applied Sciences Volume 11 Issue 16 Applied Sciences, Vol 11, Iss 7593, p 7593 (2021) |
| ISSN: | 2076-3417 |
| Popis: | We propose a simple and robust HSV color-space-based algorithm that can automatically extract object position information without human intervention or prior knowledge. In manufacturing sites with high variability, it is difficult to recognize products through robot machine vision, especially in terms of extracting object information accurately, owing to various environmental factors such as the noise around objects, shadows, light reflections, and illumination interferences. The proposed algorithm, which does not require users to reset the HSV color threshold value whenever a product is changed, uses ROI referencing method to solve this problem. The algorithm automatically identifies the object’s location by using the HSV color-space-based ROI random sampling, ROI similarity comparison, and ROI merging. The proposed system utilizes an IoT device with several modules for the detection, analysis, control, and management of object data. The experimental results show that the proposed algorithm is very useful for industrial automation applications under complex and highly variable manufacturing environments. |
| Databáze: | OpenAIRE |
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