Design of an Automatic Light Intensity Control System and Image Processing Algorithm for the Development of an Assistive Drug Screening Device

AbstractThis study was carried out to develop a prediction model for soluble solid content (SSC) of intact chestnut and to detect internal defects using nuclear magnetic resonance (NMR) relaxometry and magnetic resonance imaging (MRI). Inversion recovery and Carr–Purcell–Meiboom–Gill (CPMG) pulse sequences used to determine the longitudinal (T1) and transverse (T2) relaxation times, respectively. Partial least squares regression (PLSR) was adopted to predict SSCs of chestnuts with NMR data and histograms from MR images. The coefficient of determination (R2), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD), and the ratio of error range (RER) of the optimized model to predict SSC were 0.77, 1.41 °Brix, 1.86, and 11.31 with a validation set. Furthermore, an image-processing algorithm has been developed to detect internal defects such as decay, mold, and cavity using MR images. The classification applied with the developed image processing algorithm was over 94% accurate to classify. Based on the results obtained, it was determined that the NMR signal could be applied for grading several levels by SSC, and MRI could be used to evaluate the internal qualities of chestnuts.

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An Image Processing Algorithm to Find New and Old Bruises

Applied Engineering in Agriculture ◽

10.13031/2013.25799 ◽

1995 ◽

Vol 11 (5) ◽

pp. 751-757 ◽

Cited By ~ 10

Author(s):

J. A. Throop ◽

D. J. Aneshansley ◽

B. L. Upchurch

Keyword(s):

Image Processing ◽

Processing Algorithm ◽

Image Processing Algorithm

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Implementation of a Digital Image Processing Algorithm on a Colibri IMX6 Embedded Industrial System for Optical Mark Recognition

Proceedings of the 3rd Brazilian Technology Symposium ◽

10.1007/978-3-319-93112-8_2 ◽

2018 ◽

pp. 9-22

Author(s):

Carlos Herrera ◽

Stephany Del Campo ◽

Abel Dueñas ◽

Julio León ◽

Guillermo Kemper ◽

...

Keyword(s):

Image Processing ◽

Digital Image Processing ◽

Digital Image ◽

Processing Algorithm ◽

Industrial System ◽

Image Processing Algorithm ◽

Optical Mark Recognition

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Image Processing Algorithm for Weight Estimation of Dairy Cattle

Journal of Biosystems Engineering ◽

10.5307/jbe.2011.36.1.48 ◽

2011 ◽

Vol 36 (1) ◽

pp. 48-57 ◽

Cited By ~ 1

Author(s):

Kwang-Wook Seo ◽

Hyeon-Tae Kim ◽

Dae-Weon Lee ◽

Yong-Cheol Yoon ◽

Dong-Yoon Choi

Keyword(s):

Image Processing ◽

Dairy Cattle ◽

Processing Algorithm ◽

Weight Estimation ◽

Image Processing Algorithm

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Marker-guided auto-landing on a moving platform

International Journal of Intelligent Unmanned Systems ◽

10.1108/ijius-10-2016-0008 ◽

2017 ◽

Vol 5 (1) ◽

pp. 28-42 ◽

Cited By ~ 4

Author(s):

Iryna Borshchova ◽

Siu O’Young

Keyword(s):

Image Processing ◽

Visual Servoing ◽

Low Cost ◽

Field Tests ◽

Processing Algorithm ◽

Prototype System ◽

Image Processing Algorithm ◽

Suggested Approach ◽

Content Type ◽

Moving Platform

Purpose The purpose of this paper is to develop a method for a vision-based automatic landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving platform. The landing system must be highly accurate and meet the size, weigh, and power restrictions of a small UAV. Design/methodology/approach The vision-based landing system consists of a pattern of red markers placed on a moving target, an image processing algorithm for pattern detection, and a servo-control for tracking. The suggested approach uses a color-based object detection and image-based visual servoing. Findings The developed prototype system has demonstrated the capability of landing within 25 cm of the desired point of touchdown. This auto-landing system is small (100×100 mm), light-weight (100 g), and consumes little power (under 2 W). Originality/value The novelty and the main contribution of the suggested approach are a creative combination of work in two fields: image processing and controls as applied to the UAV landing. The developed image processing algorithm has low complexity as compared to other known methods, which allows its implementation on general-purpose low-cost hardware. The theoretical design has been verified systematically via simulations and then outdoors field tests.

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