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Speed limit traffic sign recognition plays a key role in intelligent transport system (ITS), especially in driver assistant system (DAS) and intelligent autonomous vehicles (IAV). Although traffic signs are clearly defined in color, shapes for easily detecting purpose, an excellent traffic sign detection system still be a challenge for researchers and manufactures because of the strict requirements...
Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of the input video signals. This integrated solution defines an image descriptor that reflects the global motion information over...
In this study, the similarity between different art movements is investigated. For this purpose, five different art movements are selected and thirty paintings are determined from different painters. By using these paintings, the similarity between paintings inside art movements and from other modern art movements are shown and classified by using mathematical methods. Computational methods are used...
In this paper, we propose a compact image steganalysis method for the LSB-matching steganography, in which a feature vector composed by only 12 elements is extracted from the image. We analyze the statistical artifact occurred in images when a secret data is embedded in it by the LSB-matching steganography. We selected 12 most relevant features based on the probability density function (PDF) of difference...
Recognition of human climbing fences in trans-former substations is very essential in a power substation. This paper proposed an innovative and practical human climbing fences detection method based on image processing. At first, the Gaussian Mixture Model background modelling algorithm is exploited to detect motion objects under a view of fix surveillant camera in a power substation. After obtaining...
Safety helmet wearing detection is very essential in power substation. This paper proposed a innovative and practical safety helmet wearing detection method based on image processing and machine learning. At first, the ViBe background modelling algorithm is exploited to detect motion object under a view of fix surveillant camera in power substation. After obtaining the motion region of interest, the...
This paper presents a finger-spelling recognition system focusing on Thai finger-spelling sign language, derived from the computer vision, using SVM. In this study, global and local features were extracted from input finger images. In order to develop the recognition system, 15 Thai alphabet characters were collected from five hand signers, totally 375 character pictures, in order to train the system...
Searching through and selecting data sets from large traffic databases with sensor information is often a cumbersome manual process. In this paper we present an idea that may dramatically fasten and streamline this process. The idea is to build a fast search index (COSI: COngestion Search engIne) based on meta data in combination with features from the traffic patterns along routes. Instead of ploughing...
The paper presents a unique combination of texture feature extraction techniques which can be used in image texture analysis. Setting the prime objective of classifying different texture images, the Local Binary Pattern (LBP) and a modified form of Gray Level Run Length Matrix (GLRLM) are implemented initially. The next phase involves use of combination of the former two methods to extract improved...
Hypertension poses a serious atherosclerotic risk as it causes both macro- and micro circulation damage. Nailfold capillaroscopy is a valuable yet simple tool to assess microcirculation of blood capillaries. This technique is important in detecting early occurrences of scleroderma spectrum disorders and evaluating Raynaud's Phenomenon. Here it is used in detecting hypertension in patients. Current...
Faces express many social indications, including gender, ethnicity, age, expression and identity, most of them have drawn thriving attention from various research communities, for instance neuroscience, computer science and psychology. In this paper, we propose a new approach to classify gender and ethnicity by merging both texture and shape features extracted from face images. Gabor filter is used...
The growth of marine renewable energy and marine protected areas in France leads to a growing need for animal population knowledge at sea. Offshore energy generator projects (wind turbines for example) must obey these regulations and show their harmlessness to the environment, particularly to the wildlife and to protected species, which are vulnerable and threatened. This paper presents a supervised...
In this paper a method for multiple human detection in the image has been presented. This method uses differential evolution (DE) algorithm to improve window position detection speed and HOG-LBP algorithm for feature extraction. Fitness function for DE algorithm is SVM and in the final state, a postprocessing on detected windows by DE algorithm is performed. This method has been tested on INRIA datasets...
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...
The image features play an important role in object detection and recognition, the method of object detection based on Histogram of Oriented Gradient(HOG) for its good detection result receives extensive attention to many researchers. This article describes the approaches to Histogram of Oriented Gradient and support vector machine, focusing on studying the HOG feature and application, detailing the...
The research of facial beauty is an interdisciplinary topic involved in psychology, aesthetics, computer version and machine learning. In this paper, we propose several methods to assess facial beauty under unconstrained conditions. Our main works are as follows: First, we apply the local binary pattern (LBP) descriptor in different bins for face representation. We tried different types of LBP methods...
Traffic light detection plays an important role in intelligent transportation system, and many detection methods have been proposed in recent years. However, illumination variation effect is still of its major technical problem in real urban driving environments. In this paper, we propose a novel vision-based traffic light detection method for driving vehicles, which is fast and robust under different...
QR codes have become useful and efficient data storage tools which are exploited in many commercial applications including product tracking, website redirection, etc. A QR code is a 2-dimensional barcode localised through three finder patterns (three squares characterised by a series of alternative black and white modules at ratios 1∶1∶3∶1∶1) placed in its three corners. QR codes are generally placed...
Computer aided diagnosis is the most predominant research in computer vision. While considering the lumbar Magnetic Resonance Images (MRIs), identification of pathologies is a complex task as the size of the soft tissues may vary. Before recognizing the injury in the soft tissue, it is necessary to identify in which soft tissue, the pathology occurs. In order to address this issue, the classification...
Affective computing has become a growing field of research activities due to its wide use of application in human computer interface. Emotion recognition is one of the state-of-the-art techniques in determining current psychological state of human being. Human emotions are very overlapping in nature and thus it needs an efficient feature-extractor and classifier assembly. This paper reports a novel...
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