Perbandingan Teknik Klasifikasi Fast Null-space Based Linear Discriminant Analysis (FNLDA) dan Direct Linear Discriminant Analysis (DLDA) dalam Pengenalan Citra Multimodal Wajah atau Pembuluh Darah di Telapak Tangan
Comparison of Fast Null-space Based Linear Discriminant Analysis (FNLDA) and Direct Linear Discriminant Analysis (DLDA) Classification Techniques in Face Multimodal Image Recognition or Blood Vessels in the Palms
DOI:
https://doi.org/10.33019/jurnalecotipe.v9i1.2867Keywords:
DLDA, face recognition, FNLDA, multimodal image, palm vein recognition, Multimodal Image, DLDA, FNLDA, Palm Vein Recognition, Face RecognitionAbstract
The biometric-based pattern recognition system aims to get high recognition accuracy. In real applications, generally, the system is a unimodal system that has several drawbacks. Multimodal systems can overcome those shortcomings. Different modalities are better suited for different applications. Previous studies tested the level of image recognition of palm vein by using local feature descriptors. In this paper, we compare the performance of classification techniques based on Linear Discriminant Analysis, namely Fast Null-space based Linear Discriminant Analysis (FNLDA) and Direct Linear Discriminant Analysis (DLDA) to recognize a person based on multimodal images of the face or palm vein. The image representation of the face or palm vein from the feature extraction step is used to obtain the image feature vector. Then, the data are matched and the recognition accuracy of the tested classification technique can be determined. Results show that the performance of the FNLDA classification technique is better for recognizing a person based on multimodal images of the face or blood vessels in terms of the level of recognition accuracy.
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