A Portable Cattle Tagging Based on Muzzle Pattern

This research focuses on developing an Android-based cattle identification system that is applicable and easy to use. This system uses a Scale Invariant Feature Transform (SIFT) algorithm to extract features from the muzzle images, and Random Sample Consensus (RANSAC) algorithm to eliminate features...

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Veröffentlicht in:International journal of interactive mobile technologies 2020-08, Vol.14 (13), p.134
Hauptverfasser: Indrabayu, Indrabayu, Nurtanio, Ingrid, Areni, Intan Sari, Bugiwati, Sri R.A, Bustamin, Anugrayani, Rahmatullah, Muhammad
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container_end_page
container_issue 13
container_start_page 134
container_title International journal of interactive mobile technologies
container_volume 14
creator Indrabayu, Indrabayu
Nurtanio, Ingrid
Areni, Intan Sari
Bugiwati, Sri R.A
Bustamin, Anugrayani
Rahmatullah, Muhammad
description This research focuses on developing an Android-based cattle identification system that is applicable and easy to use. This system uses a Scale Invariant Feature Transform (SIFT) algorithm to extract features from the muzzle images, and Random Sample Consensus (RANSAC) algorithm to eliminate features incompatibility. The system is experimented with four threshold values, i.e. 10, 15, 20, and 30 using a total data of 460 muzzle images.  In the first experiment, 3 images from each individual are used in the training stage and 2 images are used as the data test. In the second experiment, 5 images from each cattle are used in the training stage and 5 images are used as the data test. Data used in training stage are 244 images and in testing stage is 816 images. From the experiment, the highest accuracy rate is 98.1% with threshold values of 15 and 20. The execution time is also calculated to measure the processing time of the system. The average time taken to store an image to the database is 1.3 seconds. The main contribution of this research is technology implementation and more portable muzzle identification for local cattle in Makassar.
doi_str_mv 10.3991/ijim.v14i13.13237
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