The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Unsupervised image segmentation is an important and difficult technique in pattern recognition. In this paper, we propose an interesting region merging algorithm for segmentation of natural images. It consists of two steps: first forming initial over-segmentation by the Connected Coherence Tree Algorithm (CCTA), and then merging the primitive regions in terms of their similarity and feature in the...
Vein image recognition based on modeling shape or geometrical layout of feature points is generative approach, and the performance is usually limited by segmentation error due to poor vein image quality. This paper instead proposes to model the discriminative appearance of local image patch using the vocabulary tree model. The discriminative approach is further extended to consider the geometrical...
Several citizen service databases such as, police, national citizen identity, passport and vehicle registration, store both biographical and biometric information containing huge number of records. Achieving scalability and high accuracy for a 1:N person identification task on these databases is a huge challenge. In this work, we propose to use complementary information present in the biographical...
In this paper we tackle the problem of subgraph isomorphism detection on large graphs, which may commonly be intractable, even with state of the art algorithms. Rather than competing with other matching algorithms, we define enhancements that can be used by (almost) any subgraph isomorphism algorithm, both current and future. These enhancements consist of a number of topological features to be added...
In this paper a new variation of Support Vector Machines (SVM) is introduced. The proposed method is called Subclass Support Vector Machine (SSVM) and makes use of principles from Discriminant Analysis field using subclasses. The major difference over SVM is that it takes into account the existence of subclasses in the classes and tries to minimize the distribution of the samples within each subclass...
With the urgent demand in information security, biometric feature-based verification systems have been extensively explored in many application domains. However, the efficacy of existing biometric-based systems is unsatisfactory and there are still a lot of difficult problems to be solved. Among many existing biometric features, palmprint has been regarded as a unique and useful biometric feature...
Texture analysis algorithms are employed in many computer vision applications. A group of high performing texture algorithms are based on the concept of local binary patterns (LBP) which describe the relationship of pixels to their local neighbourhood. LBP descriptors are invariant to intensity changes and rotation invariance is simple to derive. In addition, LBP features can be calculated for different...
Iris recognition in less constrained environments is challenging due to the degraded iris images. This paper proposes a novel method fusing multiple cues for iris recognition in the non-ideal imagery. The covariance matrices are used to represent local iris texture property, which capture the correlation of spatial coordinates, intensities, 1st and 2nd-order partial derivatives. The covariance matrices...
This conference paper investigates the possibility of using on-line handwritten signatures for biomedical biometry. More specifically, features extracted from sigma-lognormal representations of signatures are applied to the problem of brain stroke susceptibility assessment. The area under the receiver operating characteristic curve (AUC) is used to evaluate the predictability of the most important...
This paper explores the utilization of product graph for spotting symbols on graphical documents. Product graph is intended to find the candidate subgraphs or components in the input graph containing the paths similar to the query graph. The acute angle between two edges and their length ratio are considered as the node labels. In a second step, each of the candidate subgraphs in the input graph is...
Based on the consideration that multiset integrated canonical correlation analysis (MICCA) does not include the class information of the samples, this paper presents a discriminative learning version of MICCA, called discriminative-analysis of multiset integrated canonical correlations (DMICC). The extracted features by DMICC not only contain the class information of training samples, but also possess...
The entire process of face detection, identification and localization of faces should preferably be almost orientation or rotation invariant. The present paper aims to design one optimal Back Propagation (BP) Network model to perform these face identification tasks. The task is partially independent of orientation or rotation of the faces in the image. Also the identification rate of the faces is...
In this paper we focus on the automatic identification of bird species from their audio recorded song. Bird monitoring is important to perform several tasks, such as to evaluate the quality of their living environment or to monitor dangerous situations to planes caused by birds near airports. We deal with the bird species identification problem using signal processing and machine learning techniques...
In the last years, face verification has gained a great interest in the pattern recognition community and in many application fields. It is among the most attractive research areas because face images can be captured in a non-intrusive way. Many algorithms have been developed in this area, among them the Principal Component Analysis (PCA) is a typical face based technique which considers face as global...
This paper proposes an adaptive integration method of reconstruction errors obtained from different point of view. There are some methods for integrating local and global processing. However, integration parameters are fixed for all test samples though effective parameters are different for every sample. Therefore, we select adaptively the parameters from only a test image. In static image recognition,...
Palmprint recognition has attracted much attention in recent years. Many algorithms based texture coding achieve high accuracy. However they are still sensitive to local unsteady region introduced by variations of hand pose and other conditions. In this paper we proposed a novel feature extraction algorithm, namely binary contrast context vector (BCCV), to represent multiple contrast distribution...
This paper proposes to perform palmprint identification with Hidden Markov Models (HMM). Palmprint identification, as an emerging biometric technology, has been extensively investigated in the last decade. Due to its low-price capture device, fast implementation speed and high accuracy, palmprint identification is very competitive in biometric research area. Currently, the majority of literatures...
In pattern recognition is necessary to have a number of features to identify each class. This article presents approaches for feature selection and classification in pattern recognition in digital images using intelligent algorithms. The question to work, a theoretical framework and related work on the subject are developed, experiments are proposed and results are shown.
This paper deals with the automated bird species identification problem, in which it is necessary to identify the species of a bird from its audio recorded song. This is a clever way to monitor biodiversity in ecosystems, since it is an indirect non-invasive way of evaluation. Different features sets which summarize in different aspects the audio properties of the audio signal are evaluated in this...
Recently, hyper-spectral facial image capturing techniques have opened a new door for creating innovative techniques aiming to improve these systems features. In our work, we have developed a verification approach based on Principal Component Analysis, and doing channel fusion (data fusion), in particular 5, 13, 14, 16, 24, 33, and 34 channels, reaching an Equal Error Rate of 97.37%; showing a good...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.