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This paper aims to present a novel method for automatic target recognition based on synthetic aperture radar (SAR) images. In order to describe a region of interest (target area), we use a saliency attention model. Then, the produced saliency map is used as a mask on SAR image in order to separate the ground target from the background. After that, we calculate the scale invariant feature transform...
Biometrie systems face several limitations like low accuracy, less robustness, low applicability and non-universality which can be minimized by the adoption of Fusion at different levels of Biometric systems. Fusion can be applied at sensor level, features level, score level as well as decision level. In this paper, we have compared the performance of a Face Recognition system without fusion and with...
Water quality operative control is considered when chemical analysis is possible. In this paper, new information-instrumental technology is proposed. This technology is based on combined use of optical instrumental means and recognition algorithms of spectral images. Adaptive multi-functional system is proposed to be as tool for operative diagnosis of hydro-chemical processes. This system has two...
Eye state recognition is still challenging in the field of computer vision. Many researchers have reported that their methods can work well with frontal face views, but not with variations of head poses. Some have described that their methods deal effectively with head pose problems, but the systems are complex to implement and consume a lot of processing time. In this paper, a novel method of eye...
Humans are trying to interact with the computer via touch screen, smart-phones, audio and video. A computer get information from the human via an interface and likewise, a human recognize an information from the computer via an interface. Facial expression recognition is a key element in a human communication. In order to promote the man and machine interaction, a framework is proposed for the facial...
Text in natural scenes provides many information for peoples and presents an essential tool to interact with their environment. Therefore, recognizing text existing in camera-captured images has become an important issue for many researches in the last decades. Currently, there isn't any available dataset of Arabic script text images in the wild. Since our aim is to help the research community in...
Humans are capable to produce thousands of facial actions during communication that vary in intensity, complexity and meaning. The purpose of this paper is to recognize the human emotions in terms of happy, sad, surprise, neutral and disgust. Its aim is to recognize the facial expression stored in a database. It uses a set of single static image with different expression labels as the training database...
Face recognition methods are evaluated against face image databases. Recent face image databases provide an evaluation protocol for an impartial comparison and assessment of where a facial recognition algorithm stands compared to other methods. Unfortunately, many authors test their facial recognition methods using either restricted face databases, random subsets from public databases, or do not follow...
We presented a new algorithm of underwater bubble recognition, which employs background modeling, image segmentation and pattern recognition. After obtaining underwater bubble images, we can separate single bubble from it manually and construct the database. Having computed Hu moment of samples for training and test, we can get the threshold and store. Then inputting the other images of sample, we...
Recently, there has been an explosion of cloud-based services that enable developers to include a spectrum of recognition services, such as emotion recognition, in their applications. The recognition of emotions is a challenging problem, and research has been done on building classifiers to recognize emotion in the open world. Often, learned emotion models are trained on data sets that may not sufficiently...
Although some developments have been achieved in finger vein recognition recently, the image deformation problem has received relatively less attention and still intractable. In this paper, the reason and the harmfulness of this problem are analyzed firstly. And then, a deformable finger vein recognition framework is proposed to deal with this problem, consisting of the improved vein PCA-SIFT feature...
This paper presents an image representation approach which is based on matrix factorization in the complex domain and called exemplar-embed complex matrix factorization (EE-CMF). The proposed EE-CMF approach can very effectively improve the performance of facial expression recognition. Moreover, Wirtinger's calculus was employed to determine derivatives. The gradient descent method was utilized to...
The main aim of recognising gestures is to build a system that can identify human gestures that are specific and then to use them to put forth desired information to the device. By using mathematical algorithms, human gestures can be interpreted. This is referred to as Gesture Recognition. Mudra is an expressive form of gesture that is mainly used in Indian classical dance form where the gesture is...
Palmprint is a unique and reliable biometric characteristic with high usability. Many works have been carried out on this field, during the past decades. Different algorithms and systems have been proposed and built successfully. Multispectral or hyperspectral palmprint imaging and recognition can be a potential solution to these systems because it can acquire more discriminative information for personal...
Trademark retrieval systems have been a well researched field however majority of these researches have been done on device trademarks and do not consider the presence of text embedded within trademark images as in case of composite marks. In this work a unified retrieval system has been proposed and implemented for composite trademarks. The technique is invariant to font size, font style and orientations,...
In recent years, there has been significant work in effective recognition of human facial expression. In this paper, we consider a new method for facial expression recognition, based on structural differences. The differences are regulated based on comprehensive laws for every expression. This article uses the Fuzzy Nero algorithm to classify support machines that have close fuzzy separation. With...
This paper proposes an entity recognition system in image documents recognized by OCR. The system is based on a graph matching technique and is guided by a database describing the entities in its records. The input of the system is a document which is labeled by the entity attributes. A first grouping of those labels based on a function score leads to a selected set of candidate entities. The entity...
The task of classifying videos of natural dynamic scenes into appropriate classes has gained a lot of attention in recent years. The problem especially becomes challenging when the camera used to capture the video is dynamic. In this paper, we analyse the performance of statistical aggregation (SA) techniques on various pre-trained convolutional neural network(CNN) models to address this problem....
Scene recognition is an important and challenging task in computer vision. We propose an end-to-end pipeline by combing convolutional neural networks (CNNs) with explicit attention model to determine several meaningful regions of original images for scene recognition. In the proposed pipeline, the spatial transformer network is leveraged as the attention module, which can automatically learn the scales...
Iris is one of the popular biometrics that is widely used for identity authentication. Different features have been used to perform iris recognition in the past. Most of them are based on hand-crafted features designed by biometrics experts. Due to tremendous success of deep learning in computer vision problems, there has been a lot of interest in applying features learned by convolutional neural...
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