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* This paper concentrates on binary classification problem, and by convention, the class label of the minority class is positive, and that of the majority class is negative. Abstract The class imbalance problem has been recognized in many practical domains and a hot topic of machine learning in recent years. In such a problem, almost all the examples are(More)
Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the(More)
Region of Interest (ROI) extraction is a crucial step in an automatic finger vein recognition system. The aim of ROI extraction is to decide which part of the image is suitable for finger vein feature extraction. This paper proposes a finger vein ROI extraction method which is robust to finger displacement and rotation. First, we determine the middle line(More)
Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. In this paper, (2D)² PCA is applied to extract features of finger veins, based on which a new recognition method is proposed in conjunction with metric learning. It learns a KNN classifier for each individual, which is(More)
BACKGROUND The neuronal electron microscopy images segmentation is the basic and key step to efficiently build the 3D brain structure and connectivity for a better understanding of central neural system. However, due to the visual complex appearance of neuronal structures, it is challenging to automatically segment membranes from the EM images. METHODS In(More)
Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are(More)
Keywords: Convolutional neural network Ensemble learning Feature learning Random forest Retinal blood vessel segmentation a b s t r a c t Segmentation of retinal blood vessels is of substantial clinical importance for diagnoses of many diseases, such as diabetic retinopathy, hypertension and cardiovascular diseases. In this paper, the supervised method is(More)
—How to improve the performance of an existing biometric system is always interesting and meaningful. In this paper, we present a novel method of score level fusion using multiple enrolled impressions to achieve higher verification accuracy of existing fingerprint systems. The main idea of the method is to build a representation of the biometric reference(More)