DETEKSI GEJALA AWAL PENYAKIT PADA IKAN BERBASIS PENGOLAHAN CITRA DIGITAL MENGGUNAKAN OPERASI MORFOLOGI CITRA (STUDI KASUS : PETERNAKAN EGI SUHENDI)

Abstract

Diseases in fish pose a serious threat to their quality and survival. This condition can cause a significant decline in fish quality, and if not addressed promptly, it can lead to mass mortality in the population of farmed fish. Early identification of symptoms of disease in fish is crucial in prevention and control efforts. One commonly used indicator is changes in the fish scales. Scales that undergo changes such as the presence of spots or unusual colors can serve as early signs of health issues in the fish. The process of identifying symptoms of disease in fish scales typically involves a series of analytical methods, ranging from image smoothing techniques using Gaussian smoothing to clarify important details, to edge detection using the Sobel algorithm to highlight structural changes in the scales. Additionally, morphological techniques such as dilation and erosion are used to improve and refine the shape and size of scales, facilitating the identification process. Subsequently, the closing process is used to fill in small holes that may form after dilation and erosion, ensuring the overall integrity of the fish scale structure is maintained.