The use of infrared images to detect ticks in cattle and proposal of an algorithm for quantifying the infestation.

This paper presents a study on the use of low resolution infrared images to detect ticks in cattle. Emphasis is given to the main factors that influence the quality of the captured images, as well as to the actions that can increase the amount of information conveyed by these images. In addition, a new automatic method for analyzing the images and counting the ticks is introduced. The proposed algorithm relies only on color transformations and simple mathematical morphology operations, thus being easy to implement and computationally light. Tests were carried out using a large database containing images of the neck and hind end of the animals. It was observed that the proposed algorithm is very effective in detecting ticks visible in the images, even if the contrast with the background is not high. On the other hand, due to both intrinsic and extrinsic factors, the thermographic images used in this study did not always succeed in creating enough contrast between ticks and cattle's hair coat. Although these problems can be mitigated by following some directives, currently only rough estimates for tick counts can be achieved using infrared images with low spatial resolution.

[1]  M Alsaaod,et al.  A field trial of infrared thermography as a non-invasive diagnostic tool for early detection of digital dermatitis in dairy cows. , 2014, Veterinary journal.

[2]  L. Grisi,et al.  Reassessment of the potential economic impact of cattle parasites in Brazil. , 2014, Revista brasileira de parasitologia veterinaria = Brazilian journal of veterinary parasitology : Orgao Oficial do Colegio Brasileiro de Parasitologia Veterinaria.

[3]  R. Wharton,et al.  THE RELATION BETWEEN ENGORGEMENT AND DROPPING OF BOOPHILUS MICROPLUS (CANESTRINI) (IXODIDAE) TO THE ASSESSMENT OF TICK NUMBERS ON CATTLE , 1970 .

[4]  S. Pyörälä,et al.  Detection of clinical mastitis with the help of a thermal camera. , 2008, Journal of dairy science.

[5]  Wolfgang Büscher,et al.  The Role of Infrared Thermography as a Non-Invasive Tool for the Detection of Lameness in Cattle , 2015, Sensors.

[6]  Eduardo Dias,et al.  Use of thermographic images to detect external parasite load in cattle , 2016, Comput. Electron. Agric..

[7]  B. Polat,et al.  Sensitivity and specificity of infrared thermography in detection of subclinical mastitis in dairy cows. , 2010, Journal of dairy science.

[8]  D C J Main,et al.  An investigation into the use of infrared thermography (IRT) as a rapid diagnostic tool for foot lesions in dairy cattle. , 2012, Veterinary journal.

[9]  D. Stajnko,et al.  Estimation of bull live weight through thermographically measured body dimensions , 2008 .

[10]  T. Pohlert.  The Pairwise Multiple Comparison of Mean Ranks Package (PMCMR) , 2016 .

[11]  A. Marcili,et al.  Geographical distribution of Amblyomma cajennense (sensu lato) ticks (Parasitiformes: Ixodidae) in Brazil, with description of the nymph of A. cajennense (sensu stricto) , 2016, Parasites & Vectors.

[12]  Gaya Prasad,et al.  DNA barcoding and surveillance sampling strategies for Culicoides biting midges (Diptera: Ceratopogonidae) in southern India , 2016, Parasites & Vectors.

[13]  K. Stafford,et al.  Non-invasive measurement of stress in dairy cows using infrared thermography , 2007, Physiology & Behavior.

[14]  John A. Basarab,et al.  The use of infrared thermography as an early indicator of bovine respiratory disease complex in calves , 2007, Research in Veterinary Science.

[15]  J. Colyn,et al.  The non-invasive and automated detection of bovine respiratory disease onset in receiver calves using infrared thermography , 2011, Research in Veterinary Science.

[16]  Craig Packer,et al.  Detection of foot-and-mouth disease virus infected cattle using infrared thermography , 2008, The Veterinary Journal.

[17]  M. A. Crane,et al.  A randomized triple blind trial to assess the effect of an anthelmintic programme for working equids in Morocco , 2011, BMC veterinary research.

[18]  I. Knížková,et al.  Infrared thermography as a tool to study the milking process: a review , 2007 .

[19]  Ilan Halachmi,et al.  Automatic assessment of dairy cattle body condition score using thermal imaging , 2013 .

[20]  Kevin W Eliceiri,et al.  NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.

[21]  Simon Gubbins,et al.  Normal variation in thermal radiated temperature in cattle: implications for foot-and-mouth disease detection , 2011, BMC veterinary research.

[22]  A. D. Kennedy,et al.  Daily variation in the udder surface temperature of dairy cows measured by infrared thermography: Potential for mastitis detection , 2003 .

[23]  Arnold W. M. Smeulders,et al.  Vector code probability and metrication error in the representation of straight lines of finite length , 1982, Comput. Graph. Image Process..

[24]  Vanessa Peripolli,et al.  Infrared thermography in animal production: An overview , 2016, Comput. Electron. Agric..

[25]  Jayme Garcia Arnal Barbedo,et al.  A review on the main challenges in automatic plant disease identification based on visible range images , 2016 .