## 4 Conclusions  
In this study, an embedded system with reference-color-based intelligent ambient lighting is designed for image-processing-based object detection and position determination in robotic handling applications. In this system, it should be noted that an adaptive lighting process based on the detection of RGBY reference objects with color-based image processing is performed without the need for any hardware, such as an external sensor/device. Thanks to image-processing-based object detection via the provision of adaptive lighting according to the color of the workpiece in the system, energy savings in ambient lighting are maintained, and the negative effects of over-lighting are eliminated.  
Based on the experimental findings, it became evident that color choice played a pivotal role in the detection process, with yellow requiring the lowest illuminance level among the tested colors. The following yellow, green, red and blue colors were observed to require progressively higher illuminance levels. It was deduced that the detection of  
Figure 12: The minimum illuminance times required to detect RGBY reference colors (Ei = 0 lx).  
Figure 13: The required electrical lighting power values depending on the initial environmental illuminance level for the designed system.  
blue-colored objects under white lighting against a white background required higher illuminance levels. Thus, employing a blue-colored object as a reference enabled the determination of the optimal illuminance level for object detection. Within the system, successful color-based object detection was achieved at an illuminance level of approximately 50 lx, with power requirements ranging from 0 to 225 mW, contingent upon ambient lighting conditions. This underscored how an intelligent lighting system adjusts the illuminance level based on environmental factors, thereby curbing energy consumption in industrial settings. Consequently, it was evident that an intelligent lighting system ensures a minimum level of illumination tailored to environmental conditions, thus leading to reduced energy consumption in industrial settings.  
Considering some issues in the implementation of the work, some improvements could be made in the system in the future. On the platform, detection was carried out in the XY plane only with the top view and illumination, without taking into account the height of the objects. In future studies, 3D objects could be detected via illumination and image acquisition from different directions and angles. If desired, it would be possible to use other non-standard colors similar to RBGY reference colors by defining HSV color space ranges in the software. Object detection and localization operations could be performed on the images obtained via instant lighting in the form of flash in order to save more energy on platforms where only robots are used and where there is no human-eye tracking.  
Conceptualization, S.D.; Methodology, U.A. and S.D.; Software, U.A. and S.D.; Investigation, U.A.; Writing--Original Draft, U.A.; Writing--Review and Editing, S.D.; Supervision, S.D. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.