The aim of this research was to explore the possibility of capturing cow’s locomotion activity by vision and the relation between vision-based calculated trackway and visual locomotion scores. 15 selected lactating cows were scored visually varied from 1 (normal walking) to 5 (extremely lame) by four trained observers. In the mean time, side view videos were recorded when cows passing the experimental set-up freely. After image processing, the trackway information containing hoof location in the real world was calculated. The mean correlation coefficient of between the results from image analysis and the output from manually labeled hoof movement was 94.8%. It proved that the image analysis method was feasible to present the cows’ real locomotion activity. The result from 15 cows’ trackway calculation showed a correlation between cows’ trackway overlaps and visual locomotion scores. This research proved that vision techniques had great potential to be used for continuous quantification of lameness in cows.
SUMMARY In order to assess associations between claw pathologies, claw signature and cow gait, 24 dairy cows were examined during six weeks. The health of the claws was not extremely bad and only few cows had a gait score resulting in classification as lame. More detailed individual associations between claw pathologies, claw signature and cow gait will be presented at the conference. Results indicate that there is an association between gait scores and the duty cycles of different legs. Further research is needed to support these findings.
The aim of this research was to explore the possibility of capturing cows locomotion activity by vision and the relation between vision-based calculated trackway and visual locomotion scores. 15 selected lactating cows were scored visually varied from 1 (normal walking) to 5 (extremely lame) by four trained observers. In the mean time, side view videos were recorded when cows passing the experimental set-up freely. After image processing, the trackway information containing hoof location in the real world was calculated. The mean correlation coefficient of between the results from image analysis and the output from manually labeled hoof movement was 94.8%. It proved that the image analysis method was feasible to present the cows real locomotion activity. The result from 15 cows trackway calculation showed a correlation between cows trackway overlaps and visual locomotion scores. This research proved that vision techniques had great potential to be used for continuous quantification of lameness in cows.
Dairy cattle lameness treatment and control is of major importance in herd health management and productivity. Detecting pre-clinical lameness is a concern but tends to be difficult because of increasing herd size and labour costs. Automation of this detection is the main objective of the presented research project. In this paper the overall approach is explained and several techniques to assess cattle gait are explored. Only techniques which do not require the attachment of sensors or markers to each individual cow are considered. Finally, a first experimental setup for the measurement of both the spatial and the temporal cattle gait characteristics is looked to more closely. For each trial, at least 32 sequential (alternating) "hoof-down" and "hoof-up" events were measured with a camera and the coordinates were calculated. Some first results are discussed.
The objective of this research was to develop and analyze image parameters correlated with expert gait scores that are applicable for lameness detection. Experiments were done on ILVO farm in Ghent, Belgium, in August/September 2007. A camera recorded postures and movements of lactating Holstein cows. The parameters trackway overlap, hoof step time and spine arch were calculated for 10 cows. Within the evaluation it was proven that the parameters contain information that can be related to lameness. First, results showed that each image parameter had a relation to gait scores given by experts. It shows that trackway overlap, hoof step time and spine arch are useful for lameness detection. A further goal is the development of an automatic on-line lameness detection tool after analyzing more lame cows and more image parameters.
Abstract Many animal welfare traits vary on a continuous scale but are commonly scored using an ordinal scale with few categories. The rationale behind this practice is rarely stated but appears largely based on the debatable conviction that it increases data reliability. Using 54 observers of varying levels of expertise, inter-observer reliability (IOR) and user-satisfaction were compared between a 3-point ordinal scale (OS) and a continuous modified visual analogue scale with multiple anchors (VAS) for scoring lameness in dairy cattle from video. IOR was significantly better for the VAS than for the OS. IOR increased with self-reported level of expertise for the VAS, whereas for the OS it was highest for observers with a moderate level of expertise. The mean continuous scores and the mean categorical scores were highly correlated. Three times as many observers stated a preference for the VAS (n = 27) compared to the OS (n = 9) in investigating differences in lameness between herds. Contrary to common perception, these results illustrate that it is possible for a continuous cattle lameness score to be more reliable and to have greater user acceptability than a simple categorical scale. As continuous scales are also potentially more sensitive, and produce data more amenable to algebraic processing and more powerful parametric analyses, the scepticism against their application for assessing animal welfare traits should be reconsidered.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)