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دسته بندی:
بینایی ماشین - Machine vision
سال انتشار:
2022
عنوان انگلیسی مقاله:
Tuning of grayscale computer vision systems
ترجمه فارسی عنوان مقاله:
تنظیم سیستم های بینایی کامپیوتری در مقیاس خاکستری
منبع:
ScienceDirect- Elsevier- Displays, 74 (2022) 102286: doi:10:1016/j:displa:2022:102286
نویسنده:
Pavel Škrabánek
چکیده انگلیسی:
Computer vision systems perform based on their design and parameter setting. In computer vision systems
that use grayscale conversion, the conversion of RGB images to a grayscale format influences performance of
the systems in terms of both results quality and computational costs. Appropriate setting of the weights for
the weighted means grayscale conversion, co-estimated with other parameters used in the computer vision
system, helps to approach the desired performance of a system or its subsystem at the cost of a negligible or
no increase in its time-complexity. However, parameter space of the system and subsystem as extended by the
grayscale conversion weights can contain substandard settings. These settings show strong sensitivity of the
system and subsystem to small changes in the distribution of data in a color space of the processed images.
We developed a methodology for Tuning of the Grayscale computer Vision systems (TGV) that exploits the
advantages while compensating for the disadvantages of the weighted means grayscale conversion. We show
that the TGV tuning improves computer vision system performance by up to 16% in the tested case studies.
The methodology provides a universally applicable solution that merges the utility of a fine-tuned computer
vision system with the robustness of its performance against variable input data.
keywords: Computer vision | Parameter optimization | Performance evaluation | WECIA graph | Weighted means grayscale conversion
قیمت: رایگان
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