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Traditional 3D feature descriptors often utilize real-valued vectors, posing challenges in terms of computational complexity and space constraints during matching. This study introduces a novel approach for generating binary 3D feature ...

• A novel binary 3D descriptor for object matching is introduced reducing time & space.
• The method utilizes the system identification concept to binarize the feature vectors.
• Approach has been verified in human recognition ...

As a new biometric technology, ear recognition is widely used in various fields such as individual identity verification, security monitoring, and access control due to its advantages of uniqueness, stability, and ease of acquisition. To deal with ...

Automatic identity recognition from ear images is an active research topic in the biometric community. The ability to secretly acquire images of the ear remotely and the stability of the ear shape over time make this technology a promising ...

• A zero-shot cross-dataset transfer protocol.
• Competitive cross-dataset results.
• The leverage of a pipeline built on top of a pre-trained backbone.

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Smartphones contain personal and private data to be protected, such as everyday communications or bank accounts. Several biometric techniques have been developed to unlock smartphones, among which ear biometrics represents a natural and promising ...

In the past few years, deep learning-based models have been very successful in achieving state-of-the-art results in many tasks in computer vision, speech recognition, and natural language processing. These models seem to be a natural fit for ...

As an important modality for human identification, Ear based biometric has achieved a relatively mature level of development, as it faces higher challenges surrounded by the real-world applications of biometric technology. One such challenge is ...

Principal Component Analysis (PCA) has been successfully applied to many applications, including ear recognition. This paper presents a Two Dimensional Multi-Band PCA (2D-MBPCA) method, inspired by PCA based techniques for multispectral and ...

A multimodal biometric system uses more than one biometric methods of an individual to mitigate some of the drawbacks of a unimodal biometric system and improve accuracy, security, and so on. Pre-processing, ring projection, data normalisation, ...

To improve on our earlier work on single-view-based ear biometrics, an estimation method is presented for the shooting angle of an ear image based on the summation of similarity scores over a threshold within a database of known shooting angles. ...

Automatic person identification from ear images is an active field of research within the biometric community. Similar to other biometrics such as face, iris and fingerprints, ear also has a large amount of specific and unique features that allow ...

Recently, deep convolutional neural networks (CNNs) have been used for ear recognition with the increasing and available ear image databases. However, most known ear recognition methods may be affected by selecting and weighting features; this is ...

Extraction and description of image features is an active research topic and important for several applications of computer vision field. This paper presents a new noise-tolerant and rotation-invariant local feature descriptor called robust local ...

Ear recognition technology has long been dominated by (local) descriptor-based techniques due to their formidable recognition performance and robustness to various sources of image variability. While deep-learning-based techniques have started to ...

Scale invariant feature transform is a local point features extraction method. It can find those feature vectors in different scale space which are invariant for scale changes and rotations, and are flexible for illumination variations and affine ...

Achieving higher recognition performance in uncontrolled scenarios is a key issue for ear biometric systems. It is almost difficult to generate all discriminative features by using a single feature extraction method. This paper presents an efficient ...

• A comparative study of ear recognition using local binary patterns variants is done.
• A new texture operator is proposed and used as an ear feature descriptor.
• Detailed analysis on Identification and verification is conducted ...

Identity recognition using local features extracted from ear images has recently attracted a great deal of attention in the intelligent biometric systems community. The rich and reliable information of the human ear and its stable structure over ...

• Presents a comprehensive study for biometric verification performance of ears before and after surgery.

Ear characteristic is a promising biometric modality that has demonstrated good biometric performance. In this paper, we investigate a novel and challenging problem to verify a subject (or user) based on the ear characteristics after ...

A new method for Modular Neural Network optimization based on a Multi-objective Hierarchical Genetic Algorithm is proposed in this paper. The modular neural network using a granular approach and its optimization using a multi-objective ...

This paper addresses the problem of human recognition using 3D ear biometrics. Existing feature extraction and description techniques in the literature for 3D shape recognition works well with the different class of shapes, however, not for profoundly ...

We proposed a novel geometric feature extraction approach for ear image.Both the maximum and the minimum ear height lines are used to characterize the contour of outer helix.Our method achieves recognition rate of 98.33 on the USTB subset1 and of 99.6 ...