Cow Weight Estimation Using Local Adaptive Thresholding Method And Connected Component Labelling
Rosida Vivin Nahari, Novita Subagiarti, Achmad Jauhari, Riza Alfita, Kunto Aji Wibisono, Achmad Fiqhi Ibadillah, Mirza Pramudia
Rosida Vivin Nahari
Available Online December 2018.
- https://doi.org/10.2991/icst-18.2018.32How to use a DOI?
- Cow weight; Calibration; edge detection; connected component labeling
- The development of technology, information and communication provides a new alternative to predict cow weight through Image Processing. This study utilizes Image Processing in visualizing the measurement of Chest Circumference and cow body length automatically. The cow weight estimation are very dependent on cow image segmentation result. Image segmentation method used in this study is local adaptive thresholding combined with the Connected Component Labeling (CCL) method. The implementation of the Chest Circumference and Body Length endpoints in the foreground is converted into centimeters (cm) to ensure cow weight estimation can be calculated using the Lambourne formula. In this study, the accuracy of RMSE was obtained from the cow weight data taken at 150, 170 and 190 cm distance. The accuracy is 20.35, 30.77 and 23.33 respectively. This research can be contribution to development of local cattle farms in Indonesia
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Rosida Vivin Nahari AU - Novita Subagiarti AU - Achmad Jauhari AU - Riza Alfita AU - Kunto Aji Wibisono AU - Achmad Fiqhi Ibadillah AU - Mirza Pramudia PY - 2018/12 DA - 2018/12 TI - Cow Weight Estimation Using Local Adaptive Thresholding Method And Connected Component Labelling BT - Proceedings of the International Conference on Science and Technology (ICST 2018) PB - Atlantis Press SP - 148 EP - 152 SN - 2589-4943 UR - https://doi.org/10.2991/icst-18.2018.32 DO - https://doi.org/10.2991/icst-18.2018.32 ID - Nahari2018/12 ER -