A Fast Auto Exposure Algorithm for Industrial Applications Based on False-Position Method

Kiran, B. Ravi; Vardhan, G. V. N. A. Harsha

doi:10.1007/978-3-319-02931-3_58

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…В [4] и [5] предложен и реализован алгоритм автоматической коррекции экспозиции с использованием метода False-position. Алгоритм предназначен для промышленного применения, например, применяется для корректной экспозиции образцов кожи с целью обнаружения их дефектов.…”

Section: алгоритмы управления экспозициейunclassified

Research of the Exposure Time Correction Algorithm for Vision Systems

Babayan

Burkina

Muraviev

2022

Proceedings of the 32nd International Conference on Computer Graphics and Vision

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Computer vision is used in many areas, from stationary video surveillance systems to mobile robots with artificial intelligence. The ability of video sensors to automatically adapt to changes in illumination is significant for high image quality, so the development and research of exposure correction algorithms is an important problem. In the paper an exposure time correction algorithm designed for use in computer vision systems is described. There three main ways to change light sensitivity in video camera is known: controlling the camera's exposure time, changing the sensor sensitivity, and lens aperture size. Each of these approaches affects the properties of the generated images in its own way and has its own advantages and limitations. The most simple to implement approaches are often based on exposure time correction. The authors propose a heuristic algorithm based on image entropy maximization. The results of simulation and testing of the algorithm in real conditions are presented. A comparison has been made with the camera auto exposure mode. Based on the results of the research, it has been concluded that the proposed algorithm has better performance with a similar final exposure time, while it has a low computational complexity.

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Section: алгоритмы управления экспозициейunclassified

Research of the Exposure Time Correction Algorithm for Vision Systems

Babayan

Burkina

Muraviev

2022

Proceedings of the 32nd International Conference on Computer Graphics and Vision

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An Auto Exposure Algorithm Using Mean Value Based on Secant Method

Sameera

Kiran

Raju

et al. 2015

Advances in Intelligent Systems and Computing

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Automatic exposure algorithms for digital photography

Bernacki

2020

Multimed Tools Appl

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In this paper we deal with the problem of calculating Automatic Exposure (AE) in digital cameras. The main problem that often occurs when taking pictures is correct exposure setting. Typically, smartphones with built-in cameras, as well as "cheap" compact digital cameras do not offer possibility of manual exposure setting. The reason is that users do not have knowledge how to set the optimal exposure, or just simply do not want to do this. Therefore, it forces that user has to rely on automatic exposure algorithms implemented in the camera. Unfortunately, these algorithms often do not perform well what causes improperly exposed images. In this paper, new algorithms for automatic exposure are proposed with the special focus on minimizing overexposed areas in the images. We have implemented proposed algorithms and conducted experiments for their efficiency, comparing with some modern cameras or smartphones. Experimental verification (enhanced by statistical analysis) shows that proposed algorithms give statistically less overexposed areas than comparative AEs.

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A Fast Auto Exposure Algorithm for Industrial Applications Based on False-Position Method

Cited by 4 publications

References 2 publications

Research of the Exposure Time Correction Algorithm for Vision Systems

Research of the Exposure Time Correction Algorithm for Vision Systems

An Auto Exposure Algorithm Using Mean Value Based on Secant Method

Automatic exposure algorithms for digital photography

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