scholarly journals 380 Precision Management of Animals: Image Processing and Computer Vision Applications

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 137-137
Author(s):  
Isabella Condotta
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Animal Welfare ◽  
Thermal Environment ◽  
Well Being ◽  
Animal Products ◽  
Management Actions ◽  
Use Of Resources ◽  
Precision Management ◽  
Effective Use

Abstract Growing populations, rising wealth, and urbanization are translating into increased demand for animal products, which causes a need for rapid intensification of production. With that, economic pressures mount on animal producers, who are forced to increase herds’ sizes in order to be commercially feasible, limiting time of interaction with their animals. In contrast, society is demanding closer attention to the needs of individual animals and their well-being, and reduction of the environmental impact of animal production. Paying closer attention to the animal can not only positively impact animal welfare and health, but also increase the capacity of the producer to increase sustainability while still reaching production needs. That’s when Precision Management of Animals (PMA) becomes necessary: The animals become central to the system and, by automatically interpreting their behavior and physical conditions through principles and technologies of process engineering, it is possible to generate data that feeds real-time monitoring and warning systems for producers, so they can take immediate management actions when needed. This leads to better management choices that are not driven only on profits, but, instead, on the needs of the animals and their care, which leads to a more effective use of resources, including antibiotics, grains, and water; improvement of animal welfare; and a data stream that can help guide new facility designs, and genetic evaluation and selection. Image processing and computer vision are examples of technologies that have been used as non-invasive methods of data collection in swine production with multiple purposes, including weight prediction, water usage, aggressive behaviors recognition, detection of lying patterns to evaluate thermal environment, localization of animals, locomotion assessment, behavior classification, gait assessment, animal measurement, and animal counting. When coupled with novel machine learning models, they seem to be a promising approach to solve the existent problems with PMA systems development.

Heat stress: impact on livestock well-being and productivity and mitigation strategies to alleviate the negative effects

2018 ◽  
Vol 58 (8) ◽  
pp. 1404 ◽  
Author(s):  
Jay S. Johnson
Keyword(s):  
Heat Stress ◽  
Animal Welfare ◽  
Body Weight Gain ◽  
Well Being ◽  
Carcass Composition ◽  
Mitigation Strategies ◽  
Adaptive Responses ◽  
Negative Effects ◽  
Animal Products ◽  
Livestock Productivity

Heat stress (HS) is a multi-factorial problem that negatively affects livestock health and productivity and is closely linked with animal welfare. While HS may not be harmful when animals are able to adapt, the physiological changes that occur to ensure survival may impede the efficient conversion of feed energy into animal products. This adaptive response can be variable and is often based on previous HS exposure, genetics, species and production stage. When the heat load becomes too great for adaptive responses to compensate, the subsequent strain response causes reduced productivity and well-being and, in severe cases, mortality. The effects of HS on livestock productivity are well documented and range from decreased feed intake and body weight gain, to reduced reproductive efficiency and altered carcass composition and meat quality. In addition, researchers are beginning to elucidate the effects of prenatal HS on postnatal livestock performance and welfare. As knowledge of the negative impacts of HS on livestock performance and welfare increases, so will the development of effective mitigation strategies to support maintenance of productivity during times of high thermal heat loads and preserve appropriate animal welfare standards.

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

Algorithms for segmentation and recognition of objects on medical images based on chiarlet transformation and neural networks

2020 ◽  
pp. 35-45
Author(s):  
Y.A. Hamad ◽  
K.V. Simonov ◽  
A.S. Kents
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Computer Vision ◽  
Edge Detection ◽  
Medical Images ◽  
Classification Algorithms ◽  
Visual Data ◽  
Recognition Of Objects

The paper considers general approaches to image processing, analysis of visual data and computer vision. The main methods for detecting features and edges associated with these approaches are presented. A brief description of modern edge detection and classification algorithms suitable for isolating and characterizing the type of pathology in the lungs in medical images is also given.

Computer Vision and robotics in postal automation

1999 ◽  
Vol 18 (3-4) ◽  
pp. 265-273
Author(s):  
Giovanni B. Garibotto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Material Handling ◽  
State Of The Art ◽  
Short Description ◽  
The Other ◽  
Functional Requirements ◽  
Postal Automation ◽  
And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

scholarly journals Plant-based fructans for increased animal welfare: provision processes and remaining challenges

2021 ◽  
Author(s):  
A. Zimmermann ◽  
C. Visscher ◽  
M. Kaltschmitt
Keyword(s):  
Animal Welfare ◽  
Dietary Fibre ◽  
Animal Feed ◽  
State Of The Art ◽  
Public Awareness ◽  
Well Being ◽  
Glycosidic Bonds ◽  
Health Promoting ◽  
Branched Structure ◽  
Stimulation Of

AbstractFructans are carbohydrates consisting of fructose monomers linked by β-2,1- and/or β-2,6-glycosidic bonds with linear or branched structure. These carbohydrates belong to the group of prebiotic dietary fibre with health-promoting potential for humans and mammals due to their indigestibility and selective stimulation of microorganisms in the gastrointestinal tract. This makes fructans interesting mainly for healthy food as well as animal feed applications. As a consequence of a growing public awareness for animal welfare, dietary fibre and thus fructans move into the focus as a fibre-rich feeding improving not only animals’ health but also their well-being. Against this background, this paper summarises the known effects of fructans focusing on pigs and highlights the state of the art in fructan production processes from plant material as well as selected current research lines. Additionally, an attempt is made to assess the potential of European fructan production for an application as animal feed. Based on this, challenges in the field of fructan production are addressed and alternative substrates for fructans are discussed and pointed out.

scholarly journals Clay-Based Brick Porosity Estimation Using Image Processing Techniques

2019 ◽  
Vol 29 (1) ◽  
pp. 1226-1234
Author(s):  
Safa Jida ◽  
Hassan Ouallal ◽  
Brahim Aksasse ◽  
Mohammed Ouanan ◽  
Mohamed El Amraoui ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Computer Vision ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Porosity Estimation ◽  
Microscopy Images ◽  
Scanning Electron

Abstract This work intends to apprehend and emphasize the contribution of image-processing techniques and computer vision in the treatment of clay-based material known in Meknes region. One of the various characteristics used to describe clay in a qualitative manner is porosity, as it is considered one of the properties that with “kill or cure” effectiveness. For this purpose, we use scanning electron microscopy images, as they are considered the most powerful tool for characterising the quality of the microscopic pore structure of porous materials. We present various existing methods of segmentation, as we are interested only in pore regions. The results show good matching between physical estimation and Voronoi diagram-based porosity estimation.

scholarly journals Population Characteristics of Cats Adopted from an Urban Cat Shelter and the Influence of Physical Traits and Reason for Surrender on Length of Stay

Animals ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 940 ◽  
Author(s):  
Miller ◽  
Ward ◽  
Beatty
Keyword(s):  
Length Of Stay ◽  
Animal Welfare ◽  
Coat Color ◽  
Population Characteristics ◽  
Study Cohort ◽  
Potential Predictor ◽  
Use Of Resources ◽  
Stray Cats ◽  
Hazard Ratios ◽  
Physical Traits

Measures aimed at reducing the length of stay (LOS) of cats in shelters can promote animal welfare and more efficient use of resources. The extent to which variables shown to impact LOS are broadly applicable is unclear. The aim of this study was to describe a population of cats adopted from an urban shelter, and to analyze the association between potential predictor variables and LOS. A study cohort was identified retrospectively from shelter records (n = 2584), 48.8% of which were < 12 weeks old at admission, and 80.7% were stray. Among 445 cats relinquished by owners, reasons for surrender were primarily owner-related (87.2%). Overall, reason for surrender and coat color were significantly associated with LOS. Hazard ratios showed that all reasons for surrender for owner-relinquished cats were associated with a shorter LOS than stray cats and this association was significant (p < 0.05) for all except cat behavioral or medical reasons. In contrast to previous reports, white cats had a significantly (p < 0.05) longer LOS than black cats. This study highlights an important role for shelter-specific baseline data to inform and measure the effect of interventional studies aimed at improving animal welfare by reducing LOS in shelter-housed cats

scholarly journals End-To-End Computer Vision Framework: An Open-Source Platform for Research and Education

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3691
Author(s):  
Ciprian Orhei ◽  
Silviu Vert ◽  
Muguras Mocofan ◽  
Radu Vasiu
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Computer Vision ◽  
Open Source ◽  
Visual Processing ◽  
Research Field ◽  
Learning Models ◽  
Research Activity ◽  
End To End ◽  
Machine Learning Models

Computer Vision is a cross-research field with the main purpose of understanding the surrounding environment as closely as possible to human perception. The image processing systems is continuously growing and expanding into more complex systems, usually tailored to the certain needs or applications it may serve. To better serve this purpose, research on the architecture and design of such systems is also important. We present the End-to-End Computer Vision Framework, an open-source solution that aims to support researchers and teachers within the image processing vast field. The framework has incorporated Computer Vision features and Machine Learning models that researchers can use. In the continuous need to add new Computer Vision algorithms for a day-to-day research activity, our proposed framework has an advantage given by the configurable and scalar architecture. Even if the main focus of the framework is on the Computer Vision processing pipeline, the framework offers solutions to incorporate even more complex activities, such as training Machine Learning models. EECVF aims to become a useful tool for learning activities in the Computer Vision field, as it allows the learner and the teacher to handle only the topics at hand, and not the interconnection necessary for visual processing flow.

Sign in / Sign up

Export Citation Format

Share Document