Implementation of Verification and Matching E-KTP with Faster R-CNN and ORB

  • Muhammad Muttabi Hudaya Telkom University
  • Siti Saadah Telkom University
  • Hendy Irawan Telkom University
Keywords: Detection, Matching, Identity Card, KTP, ORB, Faster R-CNN

Abstract

needs a solid validation that has verification and matching uploaded images. To solve this problem, this paper implementing a detection model using Faster R-CNN and a matching method using ORB (Oriented FAST and Rotated BRIEF) and KNN-BFM (K-Nearest Neighbor Brute Force Matcher). The goal of the implementations is to reach both an 80% mark of accuracy and prove matching using ORB only can be a replaced OCR technique. The implementation accuracy results in the detection model reach mAP (Mean Average Precision) of 94%. But, the matching process only achieves an accuracy of 43,46%. The matching process using only image feature matching underperforms the previous OCR technique but improves processing time from 4510ms to 60m). Image matching accuracy has proven to increase by using a high-quality dan high quantity dataset, extracting features on the important area of EKTP card images.

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Published
2021-08-25
How to Cite
Hudaya, M. M., Siti Saadah, & Hendy Irawan. (2021). Implementation of Verification and Matching E-KTP with Faster R-CNN and ORB. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 5(4), 783 - 793. https://doi.org/10.29207/resti.v5i4.3175
Section
Artikel Teknologi Informasi