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This paper proposes a new approach for image classification by combining pyramid match kernel(PMK) with spatial pyramid. Unlike the conventional spatial pyramid matching (SPM) approach which only uses a single-resolution feature vector to represent an image, we use a multi-resolution feature vector to represent an image for SPM. We then calculate the match scores at each resolution of SPM representation...
Given their widespread use for authentication, biometricsystems are a key target for Presentation Attacks (PAs). A presentation attack is an attempt to circumvent a biometricsystem by simulating the trait of an authorized person andpresenting it to the sensor. Social dimension of biometric authenticationnourishes the interest in spoofing attacks. Dependingon motivation and availability of resources,...
Handwriting has been known to be a very strong identifying characteristic of an individual and can be considered a behavioural biometric trait. This has made hand writer identification an important area of research. In this paper, a novel offline writer identification system is proposed using ensemble of multi-scale local ternary pattern histogram features. Features are extracted at multiple scales...
This paper addresses the problem of automatic target recognition (ATR) using inverse synthetic aperture radar (ISAR) images. In this context, we propose a novel approach for feature extraction to describe precisely an aircraft target from ISAR images. In our approach, a visual attention model is adopted to separate the salient regions from the background. After that, the scale invariant feature transform...
SIMPLE (Searching Images with MPEG-7 (& MPEG-7-like) Powered Localized dEscriptors) is a model that proposes the reuse of well-established global descriptors by localizing their description mechanism on image patches located by local features' detectors. Having displayed impressive retrieval results on two different databases, in this paper we extend the family by replacing the originally picked...
One of the challenges of PET/MR is replacing CT-measured attenuation map with a MR-based, especially in the absence of bone signal in MR images. Regular MRI cannot distinguish between different tissue types based on electron density, thus, Zero Echo Time (ZTE) has been used to segment bone, air and soft tissue. In this study, we have evaluated the relationship between bone density measured in CT and...
Segmentation of optic disk (OD) is a very important step in automatic Diabetic Retinopathy screening. In this paper, we presented a robust and novel template matching algorithm for automatic detection of OD in retinal images. The size of OD area depends on camera field of view and image resolution. Based on these criteria we formulated and presented OD size estimation algorithm and it is used to create...
The pattern recognition system for biometric identification, which was presented in this paper, used mathematical and statistical approaches such as Principal Component Analysis as a feature extraction method also Cross Validation and k-nearest neighbor with Euclidean metric distance for the classification method. The proposed recognition system used face and androgenic hair as biometric traits with...
The use of multi-parameter analysis of acoustic emission signals allows identifying destructive processes not only in prestressed concrete elements but also in classical concrete and reinforced concrete members. The analysis is not based on single descriptors but on destructive processes, which may be used to evaluate structural integrity of the elements. Therefore the key question is the minimum...
In this paper, we propose a scheme for identifying the authorship of off-line handwritten documents based on a histogram-based descriptor. The idea of our work is inspired from that of the Local Derivative Patterns (LDP), that has found much success in the application of face recognition. However, to the best of our knowledge, this work is the first of its kind that utilizes them for characterizing...
This competition is aimed at classification of writer demographics from offline handwritten documents using the QUWI database. QUWI is a bilingual database comprising writing samples of same individuals in Arabic and English. This allows evaluating the performance of different systems in a more challenging multi-script environment. This paper presents the details of the competition tasks, the datasets...
In this paper, we propose two novel textural-based features for writer identification: CoHinge and QuadHinge which are based on the spatial and attribute co-occurrence of the Hinge kernel. The CoHinge feature is the joint distribution of the Hinge kernel on two different pixels of writing contours and the QuadHinge feature is the joint distribution of angles and curvature information of contour fragments...
In this paper, we present a novel scheme for text-independent online writer identification. As a first contribution, we propose histogram based features, inspired from the area of object detection, to describe the structural primitives of handwriting. Secondly, we have used sparse coding techniques to learn prototypes, that describe the general writing characteristics of the authors. To the best of...
In recent years, local texture analysis methods have gained increasing attention in many areas of image processing and computer vision. The current paper deals with iris features extraction, based on dense descriptors. A dense descriptor captures the local details, pixel by pixel over the complete image. Three different techniques were employed: Local Binary Pattern, Local Phase Quantization and Differential...
Microcalcifications are the earliest sign of breast carcinoma. Their typical size is about 1 mm, which is why it is difficult to detect for an expert. Therefore, a tool that eases their visualization becomes relevant. Segmentation gives the candidate areas that could contain microcalcifications. A preprocessing step can improve segmentation performance but the algorithm becomes database dependent...
Facial expression recognition is a long standing problem in affective computing community. A key step is extracting effective features from face images. Gabor filters have been widely used for this purpose. However, a big challenge for Gabor filters is its high dimensionality. In this paper, we propose an efficient feature called dynamic Gabor volume feature (DGVF) based on Gabor filters while with...
Given a child's and a couple's facial photos, tri-subject kinship verification aims to determine the existence of blood relation between the child and the couple. Different from existing methods which model the kinship inheritance process among three persons in separate stages and only use simple features, this work establishes a simple model inspired by genetics to measure tri-subject kinship similarity...
In this paper, we propose a new texture descriptor, completed local derivative pattern (CLDP). In contrast to completed local binary pattern (CLBP), which involves only local differences at each scale, CLDP encodes the directional variation of the local differences of two scales as a complementary component to local patterns in CLBP. The new component in CLDP, with regarded as the directional derivative...
Person recognition is a challenging research problem particularly if the images are captured at a distance and only ocular region is present. In this research, we present a framework that extracts multiple features from iris and periocular regions from near infrared images captured at a distance of 2 meters or more. Using these features and random decision forest, fusion and classification is performed...
This paper investigates precise pupil center localization in low-resolution images. Being an essential preprocessing step in many applications such as gaze estimation, face alignment as well as human-computer interaction, robust, precise, and efficient methods are necessary. We present a method for accurate eye center localization operating with images from simple off-the-shelf hardware such as webcams...
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