Side View Angle Research Articles

Using of Conspicuous of Body Angularities Type Traits to Milk Yields as Dairy Cattle Selection Preferences

Numerous papers have been published on body cattle angularities subject in a few backward decades. However, the preeminent body angularities to the milk yield are unstipulated assertively. Hence, the current odyssey was to determine the transcendence body angular of dairy cattle interrelated with the milk yield for selection preferences. In total, 121 head of Holstein cows and seven reputable cattle body angularities were engaged as samples and measured variables for investigation. The software R version 4.2.1 and RStudio was operated simultaneously to facilitate statistical analysis. Later, the principal components (PCA), correlation, and regression analysis were carried out in that order. The PCA specified the thurl angle (TLA), hock side view angle (HSA), hock back views angle (HBA), and fore udder angle (FUA) as crucial factors of body cattle angularities. Then, the correlation analysis appointed HBA and TLA in series as the best trait related to milk yields. The regression analysis was merely entrusted to the HBA as a factor for prognosticating milk yield potency. Thus, the upshot of the ongoing exploration prompted the HBA as the main priority for milk yield selection preferences, followed by TLA. Both were usable on the calf, heifer, and cow selection scheme but should be enforced regularly.

Multi-view imaging simulation of a space born TDI CCD camera and a 3D geometric reconstruction estimate

This paper proposes a multi-view imaging simulation method for a space-born TDI CCD camera, focusing on the integral time and satellite attitude calculation method of a TDI CCD camera when the imaging target is far away from the nadir point. The accuracy of the calculation method was verified by a target imaging simulation. Furthermore, a multiview stereo imaging simulation of a single camera was realized. Based on the high-precision three-dimensional (3D) building model and the simulation method, the simulation image was generated under various side swing angles and 3D angles. The generated building point cloud data was based on the belief propagation and graph-cuts stereo matching methods. Finally, we evaluated the impact of the side-view angle and stereo angle on the 3D reconstruction effects of the overall area and building façade based on the effective point percentage, root mean square, NMAD, and LE90.

Comparison of segmentation algorithms for cow contour extraction from natural barn background in side view images

Computer vision techniques are a means to extract individual animal information such as weight, activity and calving time in intensive farming. Automatic detection requires adequate image pre-processing such as segmentation to precisely distinguish the animal from its background. For some analyses such as gait analysis, a side view perspective is recommended. When using a side view angle however, the background is more difficult to control – moving objects, such as other animals may negatively impact successful image segmentation. The objective of this research was to evaluate five different background segmentation algorithms on side view images when taken against a static background (a solid transportable wall) and a dynamic background (open air, without a wall).The experiments were conducted on a commercial robotic-milking dairy farm in Israel with a herd size of 70 Israeli Holstein cows. A side view image of cow’s gait was recorded after milking when the cows exited the milking area and returned to the cowshed. From the recording database, a random selection was made of 35 frames containing a static background (solid wall) and 20 frames containing a dynamic background (natural barn environment with other cows).Five segmentation algorithms were chosen and adapted from literature to extract the cow shape from the image. The output of three algorithms gave the cow’s full body shape two identified only the contour of the cow’s body. The algorithms were compared on their ability to correctly identify the cow’s back contour line. The performance of each algorithm was quantified by comparing its outputs to a golden standard of manually labelled cow pixels in the image.The introduction of a physical wall behind the cows (static background) significantly improved the foreground segmentation results (Mean Absolute Error (MAE)=6.7±5.7pixels vs. 19.7±9.1pixels). The fourth algorithm, based on an edge detection on the background difference frame, gave the best cow back contour line segmentation results (b0=−0.4±15.5 and b1=1.00±0.07). The fifth algorithm which is based on consecutive frame differences was less accurate than the other four methods which are based on the background frame differences (MAE=16.0±5.9pixels vs. 4.1±2.2pixels, 4.3±2.2pixels, 5.6±2.8pixels and 3.7±1.4pixels respectively for the other four algorithms). The results show that the applied algorithms were not robust enough to work on side view images with dynamic backgrounds.

Emergent Approach to Circle Formation by Multiple Autonomous Modular Robots

This paper deals with the problem of circle formation by multiple autonomous robots on emergent approach. The robots in question are simple, having fan-shaped local vision consisting of three areas to detect three states in each area – whether the number of robots in an area is zero, one, or more than one. We suggest heuristic action decision rule having robots form a circle stochastically. Using computer simulation, we make it clear that view angles of the local vision and the number of robots in the arena affect circle forming process, and that the certainty of circle formation is high enough if robots have certain view angles. We describe that view angles control the distance between robots using kinematic view. The keys to designing robots to form a circle are the front-view angle for making virtual attraction force toward one robot, and the side-view angle for making equilibrium of virtual force toward two robots.

Analysis of View Angle Used in Speechreading Training of Sentences

This study examines the effects of sentence perception across three speaker viewing angles: front view (0°), quarter view (45°), and side view (90°). The performance of a female adult with postlingual hearing loss was measured for accuracy at each angle. The present study used a single-subject, alternating treatment design where three treatment angles were randomly presented in every session. The percentage accuracy levels for each session were compared to determine the most effective treatment viewing angle of the speaker. The results indicated that the side-view angle was most effective, as the percentage gain of improvement was greatest in combination with the consistent upward trend of the data points across treatment sessions. The performance at front-view and quarter-view angles was also successful. The results of this preliminary effort indicate the value of treatment for visual sentence perception at all three angles, including the nontraditionally targeted side view.

Measurement and Simulation of Potato Leaf Area Using Image Processing. II. Model Results

The objectives of this study were to validate a potato canopy architecture simulation model and use it to evaluate an image processing method of measuring potato leaf area. The model was an accurate simulation of potato canopy architecture based on simulated images and simulated leaf area measurements. The simulation model was then used to show that leaf area per volume had the greatest influence on simulated image processing-measured leaf area. Changing lamina, petiole, or side view angle had a small effect on simulated image processing-measured leaf area. Use of a 3 3 median filter affected simulated image processing-measured leaf area only for plants having leaf area greater than 0.116 m2. Changing the hardware resolution, either increasing or decreasing by a factor of four, had no significant effect on simulated image processing-measured leaf area.