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Visual saliency is an important cue in human visual system, it can identify salient region in image. Image contrast has been utilized as an effective feature to detect the salient region. The conventional contrast measures utilize both spectral and spatial properties of image in many salient region detection methods. However, they only consider the local characteristics of image region, consequently,...
The identification of bird species from their audio recorded songs are nowadays used in several important applications, such as to monitor the quality of the environment and to prevent bird-plane collisions near airports. The complete identification cycle involves the use of: (a) recording devices to acquire the songs, (b) audio processing techniques to remove the noise and to select the most representative...
We introduces a new 3-D video dataset to assess the performance of Human Activity Recognition system in indoor and outdoor environment. This dataset also help to check the performance of activity recognition algorithms against the effect of varying illumination, background and viewpoint. The available dataset for activity recognition are simple and most of them contain RGB information only as well...
Biomedical research in last decade or so has seen the development of highly accurate algorithms focused on the detection and classification of the brain tumor into malignant or benign. As a result of these advancements a new research direction has emerged which focuses on categorizing the brain tumors based on their types, such as Glioma, Metastases, and Meningioma etc. In this paper, we present a...
The images of lace textile are particularly difficult to be analyzed in digital form using classical image processing techniques. The major reasons of this difficulty emerge from the complex nature of lace which generally has different textures in its constituents like the background and patterns. In this paper, we study the behavior of Image Histogram (HistI) and Local Binary Patterns (LBP) on image...
Local Binary Pattern (LBP) is a simple yet powerful method for image feature extraction in pattern recognition and image processing. However, the LBP operator of each pixel mainly depends on its neighboring pixels and emphasizes on local information too much. From the practical viewpoint, the information is quite limited if we consider the LBP operator in isolation, especially for a large image. To...
Regarding the palms recognition system studies, despite achieving a high success rate, hygiene problems in systems with contact and problems arising from changes in the alignment of the hand pose in non-contact ones have been encountered. To resolve these problems, 3D palmprint recognition systems have been developed, however these systems have not had the opportunity to spread due to expensive technologies...
A texture descriptor based on a set of indices of degrees of local approximating polynomials is proposed in this paper. An image is split into non-overlapping patches, reshaped into one-dimensional source vectors and convolved with the polynomial approximation kernels of various degrees p. As a result, a set of approximations is obtained. For each element of the source vector, these approximations...
The Electrocardiogram (ECG) is undoubtedly the most used biological signal in the clinical world and it is a means for detection of several cardiac abnormalities. Pattern recognition, diagnostic classification of ECGs constitutes an interesting application of Artificial Neural Networks (ANNs). This paper illustrates the ability of a feed-forward back propagation using Neural Network for classify unknown...
Most of visual pattern recognition algorithms try to emulate the mechanism of visual pathway within the human brain. Regarding of classic face recognition task, by using the spatiotemporal information extracted from Spiking neural network (SNN), batch learning rule and on-line learning rule stand out from their competitors. However, the former one simply considers the average pattern within the class,...
Registration of aerial images is a necessary step as valuable information for studying; monitoring, forecasting and managing natural resources can be obtained from it. This paper presents an algorithm for registration of aerial images using orthogonal moment invariants. Initially reference aerial image and test aerial image are resized to same size and converted to gray scale and contrast enhancement...
Occurrence of high imbalance in real-world domains is a direct result of rarity of interesting events, which results in skewed datasets. Without dataset rebalancing, the learning algorithm will encounter extremely low minority class samples therefore it gets biased towards the majority class in the classification tasks. Hence properly handling the imbalanced dataset is a crucial issue in the pattern...
As an increasing number of digital images are generated, a demand for an efficient and effective image retrieval mechanisms grows. In this work, we present a new skeleton-based shape retrieval algorithm, which starts by drawing circles of increasing radius around skeleton points. Since each skeleton corresponds to the center of a maximally inscribed circle, this process results in circles that are...
This paper will focus on the issue of human body dissimilarity detection from 3D bodyscan. A new 3D human body shape descriptor is proposed as well as a global geometric shape analysis of body shape surfaces coupled with anthropometrics points. The aim of this research is then to establish a new methodology of human body morphology shapes detection in order to define the morphotypes of a given population...
Biometrics-based hand authentication is among the most popular biometrics used to automatically characterize a person especially in forensic applications. Hand recognition systems are able to confirm or deny the identity of a claimed person because they do not cause anxiety for the users. However, different individuals may have almost similar hands. Therefore, the performance of the hand verification...
In this paper the effectiveness of different classification techniques is evaluated on the performance of face recognition algorithms. Gabor wavelet and its fusion with local binary pattern (LBP) are utilized as feature extractors. Dimensionality reduction approaches, principal component analysis (PCA) and Fisher's linear discriminant (FLD), are employed to reduce the size of feature vector. The performance...
Automatic emotional state recognition from the speech signal represents a remarkable improvement in human-machine interfaces and it opens up a wide range of new applications. This turns out to be no trivial task due to the degree of difficulty inherent in the study of emotions. Traditional methods of emotional discrimination use prosodic and paralinguistic features, which are determined by a linguistic...
The generalized MMSD (GMMSD) is considered an efficient implementation of MMSD to extract discriminative information. However, a significant issue with the implementation of GMMSD is the complete recomputation of the training process when new training samples are presented. In this paper, we propose an alternative solution for feature extraction using the principles of GMMSD, which we call GMMSD2...
In this study we propose an off line system for the recognition of the handwritten numeric chains. Firstly, we realized a recognition system of the isolated handwritten digits, in this part, the study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm and fed by several parameter vectors; the objective of this operation is to determine...
Image segmentation is a fundamental process in computer vision applications. This paper presents a novel method to deal with the issue of image segmentation. Each image is first segmented coarsely, and represented as a graph model. Then, a semi-supervised algorithm is utilized to estimate the relevance between labeled nodes and unlabeled nodes to construct a relevance matrix. Finally, a normalized...
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