Computer and Computing Technologies in Agriculture VII: 7th by Daoliang Li, Yingyi Chen (eds.)

By Daoliang Li, Yingyi Chen (eds.)

The two-volume set IFIP AICT 419 and 420 constitutes the refereed post-conference court cases of the seventh IFIP TC five, WG 5.14 foreign convention on machine and Computing applied sciences in Agriculture, CCTA 2013, held in Beijing, China, in September 2013. The a hundred and fifteen revised papers provided have been rigorously chosen from a variety of submissions. They conceal quite a lot of attention-grabbing theories and purposes of knowledge expertise in agriculture, together with net of items and cloud computing; simulation versions and decision-support structures for agricultural creation; shrewdpermanent sensor, tracking, and regulate expertise; traceability and e-commerce expertise; desktop imaginative and prescient, special effects, and digital fact; the applying of data and conversation expertise in agriculture; and common info carrier expertise and repair structures improvement in rural areas.

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Additional info for Computer and Computing Technologies in Agriculture VII: 7th IFIP WG 5.14 International Conference, CCTA 2013, Beijing, China, September 18-20, 2013, Revised Selected Papers, Part II

Example text

The best body measurement was extracted by the image process to build mathematical model. In order to estimate pig weight, the model was verified to be appropriate by regression analysis. The relative error is 6%. Artificial neural network was used to make model with 3% relative error later. The pig’s body size detect and weight estimation system was designed by Fu Weisen. The coordinates of key point in two pictures were found by image matching, and three-dimensional space coordinates could be computed through stereo vision principle.

Similarly, cameras were also fastened upper the drinker for the high quality image [10]. Most time pig’s body will be straight when it is drinking. But when the temperature is high in summer, pig will scramble for the drinker, and like to lie in the drinking area. This brings a lot of troubles for image collection and pig contour extraction. With the development of digital camera, shutter speed advance greatly and reduce the requirement for pig state of motion. Even fast moving pig can be snapped clearly.

The control mechanism is not needed in pig weight estimation system, and the only output is pig weight information. Thus this chapter summaries as the following aspects: camera location, light source and image trigger method. 1 Camera Location In order to get pig body sizes as many as possible, cameras were not only set at the top of pigs, but also at the side of pigs. The camera on the top of pig could get the pig back area and the one at the side of pig is set to get pig’s body height [6]. To reduce the number of cameras, pig was put in a weight cage, and a mirror was installed on the top canted 45 degree.

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