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

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

Detection, Matching, Identity Card, EKTP, ORB, Faster R-CNN.

An EKTP image repository can be a helpful tool to assist human operators in EKTP image pair checking. But, such a repository
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 resultsin 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

Muhammad Muttabi Hudaya1
, Siti Saadah2
, Hendy Irawan3

Telkom University

25-08-2021

Fajar Bagus W

PDF

Indonesia

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