scholarly journals INFRARED CEPHALIC-VEIN TO ASSIST BLOOD EXTRACTION TASKS: AUTOMATIC PROJECTION AND RECOGNITION

2017 ◽  
Vol XLII-2/W4 ◽  
pp. 193-197
Author(s):  
S. Lagüela ◽  
M. Gesto ◽  
B. Riveiro ◽  
D. González-Aguilera
Keyword(s):  
Computer Vision ◽  
Infrared Image ◽  
Thermal Infrared ◽  
Cephalic Vein ◽  
Automatic Identification ◽  
Infrared Band ◽  
Thermographic Camera ◽  
Close Range ◽  
Vein Recognition ◽  
Thermal Infrared Imagery

Thermal infrared band is not commonly used in photogrammetric and computer vision algorithms, mainly due to the low spatial resolution of this type of imagery. However, this band captures sub-superficial information, increasing the capabilities of visible bands regarding applications. This fact is especially important in biomedicine and biometrics, allowing the geometric characterization of interior organs and pathologies with photogrammetric principles, as well as the automatic identification and labelling using computer vision algorithms.<br><br> This paper presents advances of close-range photogrammetry and computer vision applied to thermal infrared imagery, with the final application of Augmented Reality in order to widen its application in the biomedical field. In this case, the thermal infrared image of the arm is acquired and simultaneously projected on the arm, together with the identification label of the cephalic-vein. This way, blood analysts are assisted in finding the vein for blood extraction, especially in those cases where the identification by the human eye is a complex task. Vein recognition is performed based on the Gaussian temperature distribution in the area of the vein, while the calibration between projector and thermographic camera is developed through feature extraction and pattern recognition. The method is validated through its application to a set of volunteers, with different ages and genres, in such way that different conditions of body temperature and vein depth are covered for the applicability and reproducibility of the method.

scholarly journals Pan-Arctic lead detection from MODIS thermal infrared imagery

2015 ◽  
Vol 56 (69) ◽  
pp. 29-37 ◽  
Author(s):  
S. Willmes ◽  
G. Heinemann
Keyword(s):  
Sea Ice ◽  
Infrared Image ◽  
Thermal Infrared ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Surface ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Thermal Infrared Imagery ◽  
Composite Maps ◽  
Ice Leads

AbstractPolynyas and leads are key elements of the wintertime Arctic sea-ice cover. They play a crucial role in surface heat loss, potential ice formation and consequently in the seasonal sea-ice budget. While polynyas are generally sufficiently large to be observed with passive microwave satellite sensors, the monitoring of narrow leads requires the use of data at a higher spatial resolution. We apply and evaluate different lead segmentation techniques based on sea-ice surface temperatures as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS). Daily lead composite maps indicate the presence of cloud artifacts that arise from ambiguities in the segmentation process and shortcomings in the MODIS cloud mask. A fuzzy cloud artifact filter is hence implemented to mitigate these effects and the associated potential misclassification of leads. The filter is adjusted with reference data from thermal infrared image sequences, and applied to daily MODIS data from January to April 2008. The daily lead product can be used to deduct the structure and dynamics of wintertime sea-ice leads and to assess seasonal divergence patterns of the Arctic Ocean.

scholarly journals Day and Night Clouds Detection Using a Thermal-Infrared All-Sky-View Camera

2021 ◽  
Vol 13 (9) ◽  
pp. 1852
Author(s):  
Yiren Wang ◽  
Dong Liu ◽  
Wanyi Xie ◽  
Ming Yang ◽  
Zhenyu Gao ◽  
...  
Keyword(s):  
Infrared Image ◽  
Thermal Infrared ◽  
Field Of View ◽  
Detection Scheme ◽  
Detection Approach ◽  
Cloud Characteristics ◽  
Formation And Evolution ◽  
Fish Eye ◽  
Infrared Channel

The formation and evolution of clouds are associated with their thermodynamical and microphysical progress. Previous studies have been conducted to collect images using ground-based cloud observation equipment to provide important cloud characteristics information. However, most of this equipment cannot perform continuous observations during the day and night, and their field of view (FOV) is also limited. To address these issues, this work proposes a day and night clouds detection approach integrated into a self-made thermal-infrared (TIR) all-sky-view camera. The TIR camera consists of a high-resolution thermal microbolometer array and a fish-eye lens with a FOV larger than 160°. In addition, a detection scheme was designed to directly subtract the contamination of the atmospheric TIR emission from the entire infrared image of such a large FOV, which was used for cloud recognition. The performance of this scheme was validated by comparing the cloud fractions retrieved from the infrared channel with those from the visible channel and manual observation. The results indicated that the current instrument could obtain accurate cloud fraction from the observed infrared image, and the TIR all-sky-view camera developed in this work exhibits good feasibility for long-term and continuous cloud observation.

Assessment of the clumped model to estimate olive orchard evapotranspiration using meteorological data and UAV-based thermal infrared imagery

2021 ◽  
Vol 39 (1) ◽  
pp. 63-80
Author(s):  
C. Riveros-Burgos ◽  
S. Ortega-Farías ◽  
L. Morales-Salinas ◽  
F. Fuentes-Peñailillo ◽  
Fei Tian
Keyword(s):  
Meteorological Data ◽  
Thermal Infrared ◽  
Infrared Imagery ◽  
Olive Orchard ◽  
Thermal Infrared Imagery

Retrieval of the pixel component temperatures from multi-band thermal infrared image using Bayesian inversion technique

2016 ◽  
Author(s):  
Feng Xie ◽  
Honglan Shao ◽  
Zhihui Liu ◽  
Chengyu Liu ◽  
Changxing Zhang ◽  
...  
Keyword(s):  
Infrared Image ◽  
Thermal Infrared ◽  
Bayesian Inversion ◽  
Inversion Technique ◽  
Multi Band

A novel method for determination of the oil slick area based on visible and thermal infrared image fusion

2021 ◽  
Vol 119 ◽  
pp. 103915
Author(s):  
Li-Feng Wang ◽  
Li-Ping Xin ◽  
Bo Yu ◽  
Lian Ju ◽  
Lai Wei
Keyword(s):  
Image Fusion ◽  
Infrared Image ◽  
Thermal Infrared ◽  
Oil Slick ◽  
Novel Method

scholarly journals Close-Range Photogrammetry and Infrared Imaging for Non-Invasive Honeybee Hive Population Assessment

2018 ◽  
Vol 7 (9) ◽  
pp. 350 ◽  
Author(s):  
Luis López-Fernández ◽  
Susana Lagüela ◽  
Pablo Rodríguez-Gonzálvez ◽  
José Martín-Jiménez ◽  
Diego González-Aguilera
Keyword(s):  
Computer Vision ◽  
Infrared Imaging ◽  
Imaging Techniques ◽  
Population Level ◽  
Non Invasive ◽  
Close Range Photogrammetry ◽  
3D Geometry ◽  
Thermographic Imaging ◽  
Close Range ◽  
Bee Colonies

Close-range photogrammetry and thermographic imaging techniques are used for the acquisition of all the data needed for the non-invasive assessment of a honeybee hive population. Temperature values complemented with precise 3D geometry generated using novel close-range photogrammetric and computer vision algorithms are used for the computation of the inner beehive temperature at each point of its surface. The methodology was validated through its application to three reference beehives with different population levels. The temperatures reached by the exterior surfaces of the hives showed a direct correlation with the population level. In addition, the knowledge of the 3D reality of the hives and the position of each temperature value allowed the positioning of the bee colonies without the need to open the hives. This way, the state of honeybee hives regarding the growth of population can be estimated without disturbing its natural development.

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