Implementasi Metode Canny dalam Sistem Penempatan Foto Kartu Identitas Siswa Otomatis - Imam Sodik; Rakhmat Kurniawan (Forum Kerjasama Pendidikan Tinggi (FKPT), 2026)
The manual creation of student identity cards often encounters several challenges, including inaccurate photo placement, inconsistent sizing, and lengthy processing time. These issues reduce efficiency and result in non-uniform document outputs. This study aims to develop a client-side web-based system capable of detecting empty rectangular areas in identity card templates and automatically embedding student photos using OpenCV.js. The system applies the Canny Edge Detection method combined with contour analysis to identify empty box regions, while image interpolation techniques are used to proportionally adjust photo dimensions according to the detected area. Experimental results show that the proposed system has been successfully implemented and is capable of accurately detecting empty regions in high-quality documents. Based on evaluation using the Intersection over Union (IoU) method, the system achieves an average accuracy of 98.67%, indicating that the Canny method is effective in detecting photo areas. The automatic photo adjustment process produces proportionally correct and ready-to-use digital outputs. Therefore, the system improves efficiency, accuracy, and consistency in the student identity card creation process.