Optimalisasi Preprocessing untuk Peningkatan Akurasi Pengenalan Plat Nomor pada Citra Tidak Ideal
DOI:
https://doi.org/10.32492/nucleus.v3i2.3206Keywords:
Pengenalan Plat Nomor, YOLO, OCR, Perbaikan Kualitas GambarAbstract
Penelitian ini bertujuan untuk mengevaluasi performa Optical Character Recognition (OCR) dalam mengenali teks pada gambar plat nomor kendaraan yang diambil menggunakan kamera digital. Dataset yang digunakan terdiri dari 10 gambar plat nomor kendaraan dengan karakteristik gambar lalu lintas kendaraan, termasuk pencahayaan rendah, distorsi perspektif, noise, dan ukuran gambar yang kecil. Berbagai teknik perbaikan kualitas gambar diterapkan, seperti Contrast Limited Adaptive Histogram Equalization (CLAHE), Bilateral Filtering, Wavelet Denoising, Unsharp Masking, dan Super-Resolution GAN menggunakan bicubic interpolation.
Pengukuran akurasi dilakukan menggunakan dua metrik utama, yaitu Character Accuracy Rate (CAR) dan Word Accuracy Rate (WAR), dengan nilai rata-rata masing-masing sebesar 96,91% dan 90,00%. Hasil penelitian menunjukkan bahwa metode perbaikan kualitas gambar mampu meningkatkan visibilitas karakter pada plat nomor, sehingga OCR dapat mengenali teks dengan akurasi tinggi meskipun terdapat noise dan distorsi pada gambar. Penelitian ini memberikan wawasan tentang efektivitas pipeline perbaikan gambar dan OCR pada kondisi lalu lintas kendaraan, serta menjadi landasan untuk pengembangan sistem pengenalan plat nomor yang lebih baik
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