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Image retrieval is an active research area for the last two decades. This area is gaining more importance as the multimedia content over the internet is increasing. Color Texture and shape are the low level image descriptor in Content Based Image Retrieval. These low level image descriptors are used for image representation and retrieval in CBIR. This paper presents a Content Base Image Retrieval...
Decisions about cervical cancer diagnosis and classification currently require microscopic examination of cervical tissue by an expert pathologist. In the present study, which focused on full automation of this approach, we solely use nucleus-level features to classify tissues as normal or cancer. We propose Adaptive Nucleus Shape Modeling (ANSM) algorithm for nucleus-level analysis which consists...
Text detection is a difficult task due to the significant diversity of the texts appearing in natural scene images. In this paper, we propose a novel text descriptor, SPP-net, extracted by equipping the Convolutional Neural Network (CNN) with spatial pyramid pooling. We first compute the feature maps from the original text lines without any cropping or warping, and then generate the fixed-size representations...
This research presents an abnormal beat detection scheme from lead II Electrocardiogram (ECG) signals along with some improvements on feature extraction. A set of 16 features representing positions, durations, amplitudes and shapes of P, Q, R, S and T waves is proposed in this work for heart beat classification. These features carry important medical information for normal and abnormal beat detection...
In this paper, we present the principal component analysis (PCA) of shape deformations of bilateral hippocampi in Alzheimer's disease (AD) as derived in the large deformation diffeomorphic metric mapping setting. We investigated the PCA patterns (the scores and loadings) of the bilateral hippocampi for 51 subjects, 28 of which had AD while 23 were normal aging. Student's t-tests were used to select...
In this paper a new method for continuous pain detection is proposed. One approach to detect the presence of pain is by processing images taken from the face. It has been reported that expression of pain from the face can be detected utilizing Action Units (AUs). In this manner, each action units must be detected separately and then combined together through a linear expression. Also, pain detection...
ShapeNets is an image representation, which is based on shape, compact structure, hierarchical image structure and appearance characteristic of object contour. In a ShapeNets, the shape of image is a window of containing objects which can be extracted with the method of objectness. The outline of objects can also be extracted in a line boundary detection algorithm based on histogram of gradients direction,...
Interaction experience in multimedia systems can be improved by adding personalization. Current applications for building and animating characters to represent real users are typically based on pose and motion detection. For so doing, computer vision algorithms do not exploit the anatomical characteristics of the human body for improving their classification accuracy. This work presents an strategy...
A method of fish category recognition is proposed. Our novelty is in feature extraction technique, which is based on determining the curvature of the contour of fish image. The category recognition of test fish is done by a suitable linear multi-class SVM classifier. To apply our algorithm, we have developed a fish image database containing six different categories of fish. The overall accuracy of...
Detecting infrared pedestrian in outdoor smart video surveillance is always a challenging and difficult problem. Although there have been many methods based on histograms of oriented gradients (HOG) to solve this problem, they would probably fail because of shelter and poor quality of image. To overcome this problem, we propose a robust feature to describe pedestrian which is called entropy-edge weighted...
This work aims to improve the accuracy of the SVDD-based Intrusion Detection Systems. In this study we are interested by approaches using only one-class classification, namely the class of normal user sessions. Sessions are modeled by vectors of points in a finite features space. The goal of using the SVDD in anomaly detection is to find the hypersphere with a minimal volume that encloses the entire...
Tuberculosis (TB) these days is considered as a major health threat in most of the countries of the world. Bacillus, also referred to as Mycobacterium tuberculosis, is the main cause of mortality due to TB. It is reported that mortality rates of patients with tuberculosis are higher when it is not diagnosed at an early stage. At present the approaches used to diagnose TB are based on the incorrect...
Shape features are widely used in image target recognition due to their useful property of translation, rotation and scaling invariance. In this paper, low order Hu moments and other four shape features are combined together to classify different kinds of knives and guns with the support vector machine in the application of millimeter wave security imaging. Experimental results show that the combined...
Radiolarian assemblages have played a significant role as a biostratigraphic and paleoenvironmental tool used in the geological settings. These species can be used in studying sediments lacking calcareous fossils. Easy identification of these species would allow micropaleontologists to proceed further into studying the structure and way of living of these Radiolarians. RaDSS is a decision support...
Multispectral data from inexpensive, yet accurate, sensors has become readily available within the last several years and opened many possibilities for contactless biometrics applications. The Kinect v2 provides depth, RGB, and Near-Infrared (NIR) data and can be used for recognition of individuals using extracted hand regions in all three spectra. Initially, the depth data is used to extract the...
The very high resolution (VHR) images can be seen as multiview data. For better organizing and highlighting similarities and differences between the multiple views of data, a semisupervised multiview feature selection (SemiMFS) method is proposed in this paper, based on consensus and complementary principles. In SemiMFS, feature views are generated by decomposing features into multiple disjoint and...
Indirect immunofluorescence (IIF) imaging is an important technique for detecting antinuclear antibodies in HEp-2 cells and therefore employed in the diagnosis of autoimmune diseases and other important pathological conditions involving the immune system. HEp-2 cells are often categorised into six groups (homogeneous, fine speckled, coarse speckled, nucleolar, cytoplasmic, and centromere cells), which...
Feature selection is often required to select a feature subset from the original feature set of objects of very high resolution (VHR) remote sensing images. However, the majority of feature selection methods is supervised, and could fail to identify the relevant features when labeled objects are scarce. To address the problem, this paper proposes a method, efficient semi-supervised feature selection...
Expressions are commonly presented through the motions of different facial regions, thus the selection of discriminative features from prominent regions is crucial to the expression recognition. This paper proposes a novel method for facial expression recognition by exploring the most salient regions for each expression. The main contribution of this paper is using the complete feature set of expressions...
Traffic sign recognition is an important topic in driver assistant system and intelligent autonomous vehicles. Traffic sign detection is a critical step, whose performance greatly affect the performance and computation cost of traffic sign recognition. In this paper, we propose a traffic sign detection method based on a scoring SVM model. First, traffic sign color and color gradient are extracted...
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