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Gender is one of the most useful facial attributes which are detected from human face images. In this work, we introduce a new gender classification system based on features extracted by Local Phase Quantization (LPQ) operators from intensity and Monogenic images. More detailed, the LPQ features are obtained from the input image (the intensity one) and from three other Monogenic components in the...
Video surveillance systems have enabled the monitoring of complex events in several places, such as airports, banks, streets, schools, industries, among others. Due to the massive amount of multimedia data acquired by video cameras, traditional visual inspection by human operators is a very tedious and time consuming task, whose performance is affected by fatigue and stress. A challenge is to develop...
The current focus of our research is to detect and classify the plant disease in agricultural domain, by implementing image processing techniques. We aim to propose an innovative set of statistical texture features for classification of plant diseases images of leaves. The input images are taken by various mobile cameras. The Scale-invariant feature transform (SIFT) features used as texture feature...
This paper introduces a new system to identify handwritten signatures. For feature generation, we propose the Histogram of templates, while the Artificial Immune recognition System (AIRS) is used to achieve the identification task. A writer-independent strategy is proposed to train the AIRS to get an open system that can identify any new writer. Experiments are conducted on a benchmark dataset composed...
This paper presents a multiple classifier system (MCS) to identify plants species based on the texture and shape features extracted from leaf images. A diverse pool of SVM and Neural Network classifiers is trained on four different feature sets, namely, Local Binary Pattern (LBP), Histogram of Gradients (HOG), Speed of Robust Features (SURF) and Zernike Moments (ZM). Then, a static classifier selection...
Insulator is an important component in the power grid. Therefore, faulty insulator can cause a great damage to the power grid that would lead to leakage currents flowing through line supports. This leads to increase in electrical loses, voltage drop and put human safety to risk. Hence, it is very important to monitor the condition of an insulator before resulting to a great damage in the power grid...
In recent years, intelligent mathematics problem solving has aroused the interest of researchers. In the intelligent mathematics problem solving system related to high school, the classification of statistical graph is a key step. Consequently, the classification of statistical graphs has become an urgent problem to be solved. In this paper, a new method is proposed for statistical graphs classification...
This paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on...
Frame dropping is a type of video manipulation where consecutive frames are deleted to omit content from the original video. Automatically detecting dropped frames across a large archive of videos while maintaining a low false alarm rate is a challenging task in digital video forensics. We propose a new approach for forensic analysis by exploiting the local spatio-temporal relationships within a portion...
Vehicle logo recognition is an important part of vehicle identification in intelligent transportation systems. State-of-the-art vehicle logo recognition approaches typically consider training models on large datasets. However, there might only be a small training dataset to start with and more images can be obtained during the real-time applications. This paper proposes an online image recognition...
In today world the necessity for the autonomous mobile robots and vehicles is increasing. The safety autonomous moving demands the reliable and fast detection algorithms. The Histogram of Oriented Gradients (HOG) descriptors show significantly outperforms the existing feature sets for a human detection. Though the given method has a lot of type I errors. The amount of these errors can be decreased...
Target recognition is a key technology in guided weapon systems. In this paper, an algorithm of target recognition based on local part is presented for the armored target in complex background. By constructing a variable target model to identify the local part of the target, the latent support vector machine is used to find the position of the part, and the position of the whole target is identified...
Offline signature identification and verification systems encounter several challenges such as the diversity of signatories and the limited number of references. To address these problems we propose a new writer-independent system for signature identification and verification. Besides, a new feature generation scheme is proposed by using the Histogram Of Templates (HOT). The identification and verification...
Cavernous malformation or cavernoma is a kind of brain vessel abnormality that can cause serious symptoms such as seizures, intracerebral hemorrhage and various neurological deficits. It is one of the most common epileptogenic lesions that can be identified by physicians based on magnetic resonance imaging (MRI) of the brain. However, visual detection of cavernomas in a large set of brain MRI slices...
Face gender classification plays an important role in pattern recognition, and it is a challenging research direction, but the current research is not perfect. We use the MB-LBP operator to extract the facial texture feature, which can be used as the training sample of the gender classifier, and it reduces the influence of the noise in the complex facial image. In addition, we propose the method of...
Pedestrian detection is an important topic in many applications, such as intelligent transportation systems (ITSs) or surveillance. For the purpose of applications used around the clock, the work for detecting pedestrian based on thermal sensors has attracted significant attention. To achieve this, this paper proposes a LBP (local binary pattern) encoded multi-level classifier for detecting pedestrians...
Due to the variability of writing styles and to other problems related to the nature of Arabic scripts, the recognition of Arabic handwriting is still awaiting accurate results. Segmentation of Arabic handwritten words into graphemes poses a major challenge in Arabic handwriting recognition and is highly error prone. In this paper, we adopt the holistic approach which handles the whole word image...
Detection of infarcted myocardium in the left ventricle is achieved with delayed enhancement magnetic resonance imaging (DE-MRI). However, manual segmentation is tedious and prone to variability. We studied three texture analysis methods (run-length matrix, co-occurrence matrix, and autoregressive model) in combination with histogram features to characterize the infarcted myocardium. We evaluated...
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...
Automated detection and recognition of human abnormal behavior is the key problem of monitoring systems. We construct a complete system that is able to alert the human operator when a knife in hand is visible in camera views. We use RealSense 3D camera to track hands, modified MPEG-7 EHD as feature vector and none-linear SVM as classifier. In this paper, we improve the feature extraction algorithm...
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