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Development of Optical Character Recognition (OCR) system for Indian script is an active area of research today. In this paper, we are concerned with the recognition of printed Oriya script a popular Indian script. The development of OCR for this script is challenging as number of identified classes are more than 380 which includes similar looking and compound characters. This paper presents the gradient...
In today's age of automation, face recognition is a vital component for authorization and security. It has received substantial attention from researchers in various fields of science such as biometrics and computer vision. In this paper, a face recognition system using Principal Component Analysis (PCA) with Back Propagation Neural Networks (BPNN) is analysed. A neural based algorithm is presented...
An important problem in text recognition such as handwritten or character images from the text are difficult to read. The decoding of these texts has important applications in many areas. Many approaches have been proposed for solving the text recognition or classification problem. We propose an artificial neural network and genetic algorithm to solve effective text recognition problem. A hetero-associative...
We propose a discriminative compact scene descriptor for single-view cross-season place recognition. Unlike previous bag-of-words approaches which rely on a library of vector quantized visual features, the proposed scene descriptor is based on a library of raw image data (such as available visual experience, images shared by other colleague robots, and publicly available image data on the web) that...
Place recognition is a fundamental requirement for mobile robots. It is particularly needed for detecting loop closures in SLAM and to enable self-localization for mobile robots given a prior map. The multitude of existing approaches rely on appearance based methods, e.g. the extraction of interest points in terms of local extrema. It can be observed that the availability of these features is highly...
Optical Character Recognition (OCR) is the mechanical or electronic conversion of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used as a form of data entry. This paper proposes an approach to design and implement an off-line OCR system that recognizes Arabic handwritten characters; in this approach Artificial Neural Networks (ANNs) were used as...
Convolutional Neural Network (CNN) is a kind of deep artificial neural network. CNN has kinds of merits, such as multidimensional data input, and fewer parameters. However, the network always has the problem of overfitting due to lots of connection in the full connection layer. In order to overcome the overfitting problem, the denoising method is used to corrupt input data and hidden unit output which...
Off-line automatic assessment systems can be an aid for teachers in the marking process. There has been no recent work in the development of off-line automatic assessment systems using handwriting recognition, even though such systems will clearly benefit the education sector. The reason is many schools and universities in many parts of the world still use paper-based examination. This research proposes...
Emotion recognition is an important task for computer to understand the human status in brain computer interface (BCI) systems. It is difficult to perceive the emotion of some disabled people through their facial expression, such as functional autism patient. EEG signal provides us a non-invasive way to recognize the emotion of these disable people through EEG headset electrodes placed on their scalp...
Hand gesture recognition plays a vital role in human computer interaction. It is a difficult task to classify a real time video. This paper presents a dynamic hand gesture recognition method from a real time video of hand gesture. The colour space ‘YCbCr’ is used for correctly determining the skin colour. Features from real time video are then extracted using Histogram of Oriented Gradient (HOG) descriptors...
In this paper, the recognition information in aircraft images of Head-Up Display (HUD) was made using artificial neural network (ANN) and a correlation algorithm. During the flight tests, the images displayed on the HUD could be stored for later analysis. HUD images presents many aircraft data provided by its avionics system (e.g. Altitude, feet, time). Therefore, HUD images are a primary source of...
Human face recognition system is a desired technique in our daily life. It is a widely well-come technique that can all-day-long and on-line recognize a person from video cameras. To this end, we use a near infrared (NIR) camera to capture day-and-night video images for on-line human recognition. In this paper, we adopt human face sub-image attraction package in OpenCV, which is based on Haar cascade...
With growing need of Through wall imaging technology by both civil and military organization, accentuate the requirement of an effective system which is able to effectively detect the targets location, differentiate it as living or non living and classify it on the basis of how it is posing to the radar in the form of radar cross section. So far, classification of bigger targets was formulated for...
Sign language recognition (SLR) is considered a multidisciplinary research area engulfing image processing, pattern recognition and artificial intelligence. The major hurdle for a SLR is the occlusions of one hand on another. This results in poor segmentations and hence the feature vector generated result in erroneous classifications of signs resulting in deprived recognition rate. To overcome this...
In the last decade we have witnessed a huge increase of interest in data stream learning algorithms. A stream is an ordered sequence of data records. It is characterized by properties such as the potentially infinite and rapid flow of instances. However, a property that is common to various application domains and is frequently disregarded is the very high fluctuating data rates. In domains with fluctuating...
Researchers in sign language recognition customized different sensors to capture hand signs. Gloves, digital cameras, depth cameras and Kinect were used alternatively in most systems. Due to signs closeness, input accuracy is a very essential constraint to reach a high recognition accuracy. Although previous systems accomplished high recognition accuracy, they suffer from stability in realistic environment...
The Student name Identification System (SIS) proposed here was investigated for English and Thai languages combined. The proposed system recognises each name by using an approach for whole word recognition. In the proposed system, the Gaussian Grid Feature (GGF), and Modified Direction Feature (MDF), together with a proposed hybrid feature extraction technique called Water Reservoir, Loop and Gaussian...
To solve problems appear in image processing with artificial neural network hardware, such as complex input of image data, difficulty in extracting image eigenvectors, knowledge management in chaos etc., a system for image recognition and knowledge management based on the KN1A artificial neural network module was designed and developed. In this system, images can be input and pretreated easily, and...
We have developed and analyzed Independent Component Analysis (ICA), Locality Preserving Projections (LPP), Minimum Average Correlation Energy (MACE) Gabor Filters, Score Level Fusion Techniques (SLFT) for Face Recognition in the presence of various noises and blurring effects. ICA considers statistical characteristics in second order or higher order. LPP is used to generate an unsupervised neighborhood...
Face recognition at a distance is one grand challenge for security surveillance. In this paper, the face images at different distances are simulated by varying image scales (resolutions). The performances of three face recognition algorithms (matchers) are tested with variant image scales (simulating different distances) and with two spectral images (modalities). The three selected matchers are face...
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