<![CDATA[Bone fractures are one of the injuries that often occur due to accidents or excessive physical activity. Fracture examination is generally performed using radiographic imaging (X-Ray), but visual identification of bone fractures can sometimes be difficult, especially in low-quality images. This study aims to analyze the texture characteristics and detect edges on X-Ray images to aid in the identification process of bone fractures. The methods used include the Gray Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP), Sobel, Prewitt, and Roberts. GLCM is used to extract texture features in the form of Contrast, Energy, Correlation, and Homogeneity, while LBP is used to obtain local texture patterns. The Sobel, Prewitt, and Roberts method is used to detect edges in bone structures. The implementation was carried out using Python on the Google Colab platform. The results showed that fracture images had a higher contrast value and a lower homogeneity value compared to normal images. In addition, the Sobel method results in a clearer edge visualization than other methods. The combination of texture analysis and edge detection is able to provide more complete information in the identification process of bone fractures.]]>
Copyrights © 2026
