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This paper presents an automatic speaker recognition system for intelligence applications. The system has to provide functionalities for a speaker skimming application in which databases of recorded conversations belonging to an ongoing investigation can be annotated and quickly browsed by an operator. The paper discusses the criticalities introduced by the characteristics of the audio signals under...
We present a method to improve the performance of content-based image retrieval (CBIR) systems. The idea is based on the concept of query models [1], which generalizes the notion of similarity in multi-feature queries. In a query model features are organized in layers. Each succeeding layer has to investigate only a subset of the image set the preceding layer had to examine. For the purpose of performance...
Conventional speaker identification systems are already field-proven with respect to recognition accuracy. Since any biometric identification requires exhaustive 1 : N comparisons for identifying a biometric probe, comparison time frequently dominates the overall computational workload, preventing the system from being executed in real-time. In this paper we propose a computational efficient two-stage...
Common image features have too poor information for identification of forensic images of fingerprints, where only a small area of the finger is imaged and hence a small amount of key points are available. Noise, nonlinear deformation, and unknown rotation are additional issues that complicate identification of forensic fingerprints. We propose a feature extraction method which describes image information...
As the size of digitized painting collections increase, it becomes more difficult to organize and retrieve paintings from these collections. To manage search and other similar operations efficiently, it becomes necessary to organize the painting databases into classes and sub-classes. Manual tagging of these ever-increasing databases would become very costly and time consuming. The above challenging...
This work is mainly intended at identifying emotion contribution of different vowels in Telugu language. Instead of processing the entire speech signal we propose to focus only vowel parts of the utterance (/a/, /i/, /u/, /e/ and /o/). By analysing the vowels we can discriminate the emotions. In this work spectral and prosodic features are used for studying the effect of emotions on different vowels...
Biometric identification verifies user identity by comparing an encoded value with a stored value of the concerned biometric characteristic. Multimodal person authentication system is more effective and more challenging. The fusion of multiple biometric traits helps to minimize the system error rate. The benefit of energy compaction of transforms in higher coefficients is taken here to reduce the...
In this paper, we present a novel approach for recognition of human faces using Markov Random Fields (MRF) and Bayesian models. We examine the relationship between feature vectors in a close proximity system. The feature vectors are coefficients of the 2D Gabor Wavelet Transform (DWGT). The MRF is implemented to match the constraint configurations between the feature vectors. The MRFs posterior probability...
The popular i-vector approach to speaker recognition represents a speech segment as an i-vector in a low-dimensional space. It is well known that i-vectors involve both speaker and session variances, and therefore additional discriminative approaches are required to extract speaker information from the ‘total variance’ space. Among various methods, the probabilistic linear discriminant analysis (PLDA)...
The appearance of the face varies drastically when background and pose change. Variations in these conditions make Face Recognition (FR) an even more challenging and difficult task. In this paper we propose two novel techniques, viz., Gabor-Feature-based DFT Shifting (GFDS) and Skin-detection-based Background Removal, to improve the performance of the FR system. GFDS is used to detect and neutralize...
Local Binary Pattern (LBP) has been widely used for analyzing local texture features of an image. Several new extensions of LBP based texture descriptors have been proposed, focusing on improving the robustness to noise by using different encoding or thresholding schemes where the most widely known are Median Binary Patterns (MBP), Fuzzy LBP (FLBP), Local Quantized Patterns (LQP), and Shift LBP (SLBP)...
In this paper, a simple biometric scheme based on RGB retinal fundus images is proposed. First, prominent vasculature energy based feature vectors are constructed from RGB retinal fundus images to utilize the unique pattern of retinal vasculature. Next, fast normalized cross-correlation based feature matching is employed for person identification on publicly available DRIVE and STARE databases. This...
Ongoing developments in stereoscopic display technologies have led to the proliferation of huge stereo image databases. Therefore, the design of an appropriate Content Based Image Retrieval (CBIR) system for stereo images is an important emerging issue. In this paper, we propose a novel retrieval method which exploits simultaneously the spatial and cross-view dependencies of the stereo images. Within...
Automatic facial expression recognition has been drawn many attentions in both computer vision and artificial intelligence (AI) for the past decades. Although much progress has been made, facial expression recognition (FER) is still a challenging and interesting problem. In this paper, we propose a new FER system, which uses the active shape mode (ASM) algorithm to align the faces, then extracts local...
This paper presents a novel video copy detection system. The kernel of the approach is based on our proposed extended local descriptor WLD to three orthogonal planes (WLD-TOP). Indeed, in the aim to extract features vector, key-frames are generated and then a perceptual hash is performed using the WLD-TOP descriptor. The proposed method is applied on three databases and evaluated against several attacks...
The theme of work presented in this paper is a novel Iris recognition technique using partial energies of transformed iris image. To generate transformed iris images, various transforms like Cosine, Walsh, Haar, Kekre, Hartley transforms and their wavelet transforms are applied on the iris images. Feature vectors are then generated from these transformed Iris images using the concept of energy compaction...
Gender classification can play a significant role in security and surveillance system. It aids in identification of a person by recognizing its gender (male/female) from the face image only. Extracting discriminate features for male and female is a fundamental and challenging problem in the field of computer vision. In this manuscript, a combination of Approximation Face Image (AFI) with Principal...
The Internet has opened new interesting scenarios in the fields of e-commerce, marketing and on-line transactions. In particular, thanks to mobile technologies, customers can make purchases in a faster and cheaper way than visiting stores, and business companies can increase their sales volume due to a world-wide visibility. Moreover, online trading systems allow customers to gather all the required...
Several existing content-based image retrieval and classification systems rely on low-level features which are automatically extracted from images. However, often these features lack the discrimination power needed for accurate description of the image content and hence they may lead to a poor retrieval or classification performance. This article applies an evolutionary feature synthesis method based...
This paper extracts statistical features using a novel approach. The feature set locally measure the characteristics of the image. The proposed approach encodes the extracted features, from a one-pixel width window that slides horizontally the word image. We then inject the feature vector set into a recognition engine. The recognition engine is built using Hidden Markov Models Tool Kit (HTK). The...
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