An automatic ear base temperature extraction method for top view piglet thermal image

Lu, Mingzhou; He, Jinrong; Chen, Chao; Okinda, Cedric; Shen, Mingxia; Liu, Longshen; Yao, Wen; Norton, Tomás; Berckmans, Daniël

doi:10.1016/j.compag.2018.10.030

Cited by 24 publications

(9 citation statements)

References 13 publications

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“…(iv) Curve extraction technique, such as: curve skeletonization ( Jin et al, 2016 ). Furthermore, some feature extraction methods ( Lu et al, 2016 , 2018 ) may help.…”

Section: Experiments Results and Discussionmentioning

confidence: 99%

RETRACTED: Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm

2021

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Aim: Multiple sclerosis (MS) is a disease, which can affect the brain and/or spinal cord, leading to a wide range of potential symptoms. This method aims to propose a novel MS recognition method.Methods: First, the bior4.4 wavelet is used to extract multiscale coefficients. Second, three types of biorthogonal wavelet features are proposed and calculated. Third, fitness-scaled adaptive genetic algorithm (FAGA)—a combination of standard genetic algorithm, adaptive mechanism, and power-rank fitness scaling—is harnessed as the optimization algorithm. Fourth, multiple-way data augmentation is utilized on the training set under the setting of 10 runs of 10-fold cross-validation. Our method is abbreviated as BWF-FAGA.Results: Our method achieves a sensitivity of 98.00 ± 0.95%, a specificity of 97.78 ± 0.95%, and an accuracy of 97.89 ± 0.94%. The area under the curve of our method is 0.9876.Conclusion: The results show that the proposed BWF-FAGA method is better than 10 state-of-the-art MS recognition methods, including eight artificial intelligence-based methods, and two deep learning-based methods.

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“…(iv) Curve extraction technique, such as: curve skeletonization ( Jin et al, 2016 ). Furthermore, some feature extraction methods ( Lu et al, 2016 , 2018 ) may help.…”

Section: Experiments Results and Discussionmentioning

confidence: 99%

RETRACTED: Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm

2021

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“…Experiments are carried out on a set of images from LTIR dataset [12], piglet thermal image database [13] as well as OSU thermal pedestrian database [14]. The LTIR database contains sequences of different environments that include natural as well as man-made background, indoors as well as outdoors.…”

Section: Resultsmentioning

confidence: 99%

Double Thresholding with Sine Entropy for Thermal Image Segmentation

Manda¹,

Hyun²

2021

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Traditional thresholding methods are often used for image segmentation of real images. However, due to distinct characteristics of infrared thermal images, it is difficult to ensure an optimal image segmentation using the traditional thresholding algorithms, and therefore, sometimes this can lead to over-segmentation, missing object information, and/or spurious responses in the output. To overcome these issues, we propose a new thresholding technique that makes use of the sine entropy-based criterion. Moreover, we build a double thresholding technique that makes use of two thresholds to get the final image thresholding result. Besides, we introduce the sine entropy concept as a supplement of the Shannon entropy in creating threshold-dependent criterion derived from the grayscale histogram. We found that the sine entropy is more robust in interpreting the strength of the long-range correlation in the gray levels compared to the Shannon entropy. We have experimented with our method on several infrared thermal images collected from standard image databases to describe the performance. On comparing with the state-of-art methods, the qualitative results from the experiments show that the proposed method achieves the best performance with an average sensitivity of 0.98 and an average misclassification error of 0.01, and second-best performance with an average sensitivity of 0.99 and an average specificity of 0.93.

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“…Our measurements of surface eye temperature underestimated internal body temperature. Most studies that compare the surface temperature of the eye to internal temperature are based on terrestrial animals who do not reside in Arctic environments (Dunbar et al, 2009; Heath et al, 2001; Johnson et al, 2011; Lu et al, 2018; Zinn et al, 1985). These studies typically find no difference in temperature measured by thermal imagery and internal temperature measured by a thermometer (Dunbar et al, 2009; Johnson et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

The use of infrared thermography to noninvasively measure the surface temperature of polar bears during bouts of social play

2022

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Infrared thermography or thermal imagery is a noninvasive tool that can be used to measure the temperature of surfaces. Typically, thermal imagery is used for construction or military purposes but is increasingly used as a noninvasive tool in wildlife studies. We investigated the use of thermal imagery to measure surface temperature changes as a proxy for energetic expenditure. We measured the surface temperature of polar bear (Ursus maritimus) eyes, while immobilized, to determine whether the eye is a thermal window that can accurately indicate internal temperature. We found a significant difference (2.68 ± 0.41°C) between the surface temperature of the eye measured with thermal imagery and the internal rectal temperature. Additionally, we measured surface temperature changes in polar bears after bouts of social play as a proxy for energy expenditure. Mean temperature of the eye increased by 1.34 ± 0.43°C after social play, indicating that this activity increased energy expenditure. During the fasting season, polar bears rely on fat stores, and any energy expenditure beyond what is required to travel may be costly to their survival, particularly in years of low resource availability. We conclude that thermal imagery is a useful tool to noninvasively investigate the energetics of social play.

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An automatic ear base temperature extraction method for top view piglet thermal image

Cited by 24 publications

References 13 publications

RETRACTED: Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm

RETRACTED: Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm

Double Thresholding with Sine Entropy for Thermal Image Segmentation

The use of infrared thermography to noninvasively measure the surface temperature of polar bears during bouts of social play

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