Segmentasi Citra Sapi Berbasis Deteksi Tepi Menggunakan Algoritma Canny Edge Detection
DOI:
https://doi.org/10.24002/jbi.v8i1.1074Abstract
Abstract.
The determination of the cattle price is generally agreed through bargaining, it is not based on the weight of the cows being sold. Most people mainly use rough calculation. There are formulas to calculate the weight but they require perimeter information of chest size and body length. It is necessary to measure the cow manually, but in reality it is not easy to do because the cow is difficult to control. Therefore, it requires a tool that can help measure easily. This article represents the early stages of research to determine the weight of cows from the cow image acquisition. It focuses on segmentation and image processing. The image acquisition results are processed using five scenarios. The results of the evaluation show that scenario 3 (Median Blur and Canny) has the best result with the value of 230,051 MSE and 24,524 dB PSNR.
Keywords: Edge Detection, Canny, Segmentation, Cow, Image Processing
Abstrak.
Penentuan harga sapi umumnya disepakati melalui tawar menawar bukan didasarkan pada bobot sapi yang dijual. Kebanyakan menggunakan perhitungan secara kasar maupun secara kira-kira. Terdapat rumus untuk menghitung bobot sapi, rumus yang ada memerlukan informasi terkait lingkar dada dan panjang badan. Untuk mendapatkan nilai lingkar dada dan panjang badan perlu dilakukan pengukuran secara manual, namun di lapangan hal tersebut tidak mudah dilakukan karena sapi sulit dikondisikan. Oleh karena itu diperlukan alat yang dapat mengukur secara mudah. Tulisan ini merupakan tahap awal dari penelitian untuk menentukan bobot sapi dari hasil akuisisi citra sapi. Oleh sebab itu pada tahap awal ini difokuskan pada segmentasi serta pengolahan citra sapi untuk menentukan deteksi tepi terbaik yang nantinya digunakan pada penelitian selanjutnya. Citra sapi hasil akuisisi diproses menggunakan lima buah skenario deteksi tepi. Hasil evaluasi menujukkan bahwa Skenario 3 (Median Blur dan Canny) memiliki hasil yang terbaik dengan nilai MSE sebesar 230.051 dan PSNR sebesar 24.524 dB.
Kata Kunci: Deteksi Tepi, Canny, Segmentasi, Sapi, Pengolahan Citra Digital.
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