2025 |
TOMAŠEVIĆ, Darian; ŠPACAPAN, Blaž; PERUŠIĆ, Ani; PINČIĆ, Domagoj; MEDEN, Blaž; FREIRE-OBREGÓN, David; EMERŠIČ, Žiga; PEER, Vitomir ŠTRUC Peter; SUŠANJ, Diego SynPalms: Palm Identification with Synthetic Data Proceedings Article In: 16th International Conference on Ubiquitous and Future Networks (ICUFN 2025), pp. 359-361, 2025. Abstract | Links | BibTeX | Tags: biometrics, data synthesis, generative AI, palmprint recognition @inproceedings{Darian_palms25,Person identification systems based on biometric modalities, such as hand images, require extensive and diverse datasets for effective training. However, real-world datasets are often limited in size and variability, leading to poor generalization, while strict privacy regulations constrain their sharing and use. To address these issues, we introduce the SynPalms framework, an approach for generating diverse palmar-side hand images of novel synthetic identities achieved with identity mixing during sampling. We investigate the impact of synthetic data on a ResNet50-based identification system by comparing the classification accuracy obtained when training with either real-world or synthetic images, as well as when utilizing both real and synthetic data. Our experiments demonstrate the trade-off between classification accuracy and subject privacy, highlighting the potential of synthetic data for training biometric identification systems in a privacy-preserving manner. |
2009 |
Štruc, Vitomir; Pavešić, Nikola Gaussianization of image patches for efficient palmprint recognition Journal Article In: Electrotechnical Review, vol. 76, no. 5, pp. 245-250, 2009. Abstract | Links | BibTeX | Tags: biometrics, gaussianization, histogram remapping, palmprint recognition, palmprints, preprocessing @article{EV_2009_palms,In this paper we present a comparison of the two dominant image preprocessing techniques for palmprint recognition, namely, histogram equalization and mean-variance normalization. We show that both techniques pursue a similar goal and that the difference in recognition efficiency stems from the fact that not all assumptions underlying the mean-variance normalization approach are always met. We present an alternative justification of why histogram equalization ensures enhanced verification performance, and, based on the findings, propose two novel preprocessing techniques: gaussianization of the palmprint images and gaussianization of image patches. We present comparative results obtained on the PolyU database and show that the patch-based normalization technique ensures stat-of-the-art recognition results with a simple feature extraction method and the nearest neighbor classifier. |
2008 |
Štruc, Vitomir; Pavešić, Nikola A palmprint verification system based on phase congruency features Proceedings Article In: Schouten, Ben; Juul, Niels Christian; Drygajlo, Andrzej; Tistarelli, Massimo (Ed.): Biometrics and Identity Management, pp. 110-119, Springer-Verlag, Berlin, Heidelberg, 2008. Abstract | Links | BibTeX | Tags: feature extraction, palmprint recognition, palmprint verification, palmprints, performance evaluation @inproceedings{BioID2008,The paper presents a fully automatic palmprint verification system which uses 2D phase congruency to extract line features from a palmprint image and subsequently performs linear discriminant analysis on the computed line features to represent them in a more compact manner. The system was trained and tested on a database of 200 people (2000 hand images) and achieved a false acceptance rate (FAR) of 0.26% and a false rejection rate (FRR) of 1.39% in the best performing verification experiment. In a comparison, where in addition to the proposed system, three popular palmprint recognition techniques were tested for their verification accuracy, the proposed system performed the best. |