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Automatic illicit drug pill matching and retrieval is becoming an important problem due to an increase in the number of tablet type illicit drugs being circulated in our society. We propose an automatic method to match drug pill images based on the imprints appearing on the tablet. This will help identify the source and manufacturer of the illicit drugs. The feature vector extracted from tablet images...
This contribution presents a method for incorporating information given by a lane estimation system into the pedestrian recognition task. The lane in front of the vehicle is represented by a three dimensional set of points belonging to the middle of the road. A cascaded classifier solves the first stage of pedestrian recognition task delivering a list of detections in a camera image. We present a...
In this paper we describe a test of Granger non-causality from the perspective of a new measure of nonparametric conditional independence. We apply the proposed test on two synthetic nonlinear problems where linear Granger causality fails and show that the proposed method is able to derive the true causal connectivity effectively.
This paper describes a method for constructing a generative model for sets of graphs. The method is posed in terms of learning a supergraph from which the samples can be obtained by edit operations. We construct a probability distribution for the occurrence of nodes and edges over the supergraph. We use the EM algorithm to learn both the structure of the supergraph and the correspondences between...
Successive levelings are applied on document images. The residues of successive levelings are made of flat zones for which morphological transforms are described.
Registration of point clouds is required in the processing of large biological data sets. The trade off between computation time and accuracy of the registration is the main challenge in this task. We present a novel method for registering point clouds in two and three dimensional space based on Group Averaging on the Euclidean transformation group. It is applied on a set of neighboring points whose...
This paper presented a novel application of Magneto encephalography (MEG) and diffusion tensor image (DTI) on word recognition, in which the spatiotemporal signature and the neural network of brain activation associated with word recognition were investigated. The word stimuli consisted of matched and mismatched words, which were visually and acoustically presented simultaneously. Twenty participants...
In this paper we present a method for the retrieval of images in terms of perceptual similarity. Local color information is added to the shape context descriptor in order to obtain an object description integrating both shape and color as visual cues. We use a color naming algorithm in order to represent the color information from a perceptual point of view. The proposed method has been tested in...
In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a fuzzy adaptation method in order to learn and maintain the model. We use this method to build an evolving handwritten gesture recognition system. The self-adaptive nature of this system allows it to start its learning process...
Multipath interference is inherent to the working principle of a Time-of-flight camera and can influence the measurements by several centimeters. Especially in applications that demand for high accuracy, such as object localization for robotic manipulation or ego-motion estimation of mobile robots, multipath interference is not tolerable. In this paper we formulate a multipath model in order to estimate...
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incremental learner systems should not only consider the integration of knowledge from new data, but also maintain an optimum set of parameters. In this paper, we propose an approach for performing incremental learning in an adaptive...
In this paper we address the problem of automatic selection of important vessel-depicting key frames within 2D angiography videos. Two different methods of frame selection are described, one based on Frangi filter, and the other based on detecting parallel curves formed from edges in angiography images. Results are shown by comparison to physician annotation of such key frames on 2D coronary angiograms.
3D face recognition is complicated by the presence of expression variation. In this paper, we present an automatic 3D face recognition method which can differentiate the expression deformations from the interpersonal differences and recognize faces with expressions being removed. The deformations caused by expression and interpersonal difference are firstly learnt from training set, respectively....
In this paper, we propose a new algorithm for shape initialization and 3D pose alignment in Active Shape Model (ASM). Instead of initializing with average shape in previous works, we build a scatter data interpolation model from key points to obtain the initial shape, which ensures shape initialized around face organs. These key points are chosen from organs of face shape and located with a strong...
Scene text images feature an abundance of font style variety but a dearth of data in any given query. Recognition methods must be robust to this variety or adapt to the query data's characteristics. To achieve this, we augment a semi-Markov model-integrating character segmentation and recognition-with a bigram model of character widths. Softly promoting segmentations that exhibit font metrics consistent...
Automatic text detection in video is an important task for efficient and accurate indexing and retrieval of multimedia data such as events identification, events boundary identification etc. This paper presents a new method comprising of wavelet decomposition and color features namely R, G and B. The wavelet decomposition is applied on three color bands separately to obtain three high frequency sub...
Besides several other factors, radiometric differences between a reference and a floating image greatly influence the achievable accuracy of image registration. In this work we derive the magnitude of registration inaccuracy coming from changes in radiometric properties. This is done for the example of medical X-ray image registration. We therefore estimate the change of image intensity with respect...
This paper proposes a novel approach for monitoring sleep using pressure data. The goal of sleep monitoring is to detect and log events of normal breathing, sleep apnea and body motion. The proposed approach is based on translating the signal data to the image domain by computing a sequence of inter-frame similarity matrices from pressure maps acquired with a mattress of pressure sensors. Periodicity...
The proposed fingerprint enhancement algorithm utilizes power spectrum in spatial-frequency domain. The input fingerprint is partitioned and assessed as high/low quality zone by using signal-to-noise ratio (SNR) approach. For high quality zone, signal spectrum with noise suppression is used to shape an enhanced filter in frequency domain. Then, this algorithm feed neighboring enhanced zone back in...
The generation of cancelable and privacy preserving biometric templates is important for the pervasive deployment of biometric technology in a wide variety of applications. This paper presents a novel approach for cancelable biometric authentication using random multiplicative transform. The proposed method transforms the original biometric feature vector through element-wise multiplication with a...
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