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Augmented and Virtual Reality has become a highly researched subfield in the Computer Vision domain. Among various researched topics, object detection and tracking is a major field of interest, with various algorithms being developed for it. Various algorithms exist that employs different approaches to solving the problem of object detection. The approach that we take is a mixture of investigating...
Gesture is one of the most vivid and dramatic way of communications between human and computer. Hence, there has been a growing interest to create easy-to-use interfaces by directly utilizing the natural communication and management skills of humans. This paper presents a hand gesture interface for controlling media player using neural network. The proposed algorithm recognizes a set of four specific...
Gesture is one of the most vivid and dramatic way of communications between human and computer. Hence, there has been a growing interest to create easy-to-use interfaces by directly utilizing the natural communication and management skills of humans. This paper presents a hand gesture interface for controlling media player using neural network. The proposed algorithm recognizes a set of four specific...
It is extremely time consuming for researchers looking for particular events of interest to manually search in the video database. Therefore, there is enormous scope in research in the field of automatic extraction of key frames from underwater video sequences. Analysis of underwater video poses many challenges to existing techniques in computer vision including camera movement, turbidity, uneven...
This work proposes techniques for demosaicing multi-spectral images obtained from a single sensor architecture. This is a new problem. Compressed Sensing (CS) based formulations can recover images by exploiting the sparsity of the images in the wavelet domain. In this work, we improve upon existing techniques by accounting for the hierarchical (tree-structured) correlation that exists among the wavelet...
Skin detection serves as a preliminary step for number of applications like face detection, gesture recognition, internet pornographic image filtering, and surveillance system. Number of artificial neural network (ANN) based skin detection algorithms have been presented in literature which are mostly based on back propagation (BP) ANNs. This paper attempts to analyze the performance of skin classifiers...
This paper presents a program which identifies the 4-panel LCC equivalent of rice plants using image processing techniques and pattern recognition of the Backpropagation neural network. Images of the fully expanded healthy leaves were captured by digital camera and processed through RGB acquisition, color transformation, image enhancement, image segmentation and feature extraction procedures. The...
This paper presents an algorithm for tracking the torso of the user in a computer-aided breast self-examination system. The algorithm uses a neural network-based skin classifier for segmenting the skin area from the non-skin area. Using the skin mask produced by the classifier, the contours of the body are extracted and used to identify the region containing the torso of the user. The algorithm is...
Current state-of-the art supervised vessel segmentation methods require large number of feature vectors to construct a good model. In this paper, we propose a framework to optimally search for optimal features as inputs to Artificial Neural Network (ANN) trained by Scaled Conjugate Gradient (SCG). SCG is known to speed-up the learning stage in a supervised learning especially when error reduction...
Skin color is a robust cue in human skin detection. It has been widely used in various human-related image processing applications. Although many researches have been carried out for skin color detection, there is no consensus on which color space is the most appropriate for skin color detection because many researchers do not provide strict justification of their color space choice. In this paper,...
This paper introduces a fast Traffic Sign Recognition system developed for a robot, participant in the Autonomous Driving Competition in the Portuguese Festival of Robotics. The Autonomous Driving Robot performs detection and classification of traffic signs and traffic lights based on the analysis of images acquired by a camera mounted on its chassis. The proposed algorithm is composed of three processing...
The study presented aims to design and develop a face recognition system. The system utilized Viola Jones Algorithm in detecting faces from a given image. Also the system used Artificial Neural Networks in recognizing faces detected from the input. Upon experimentation the system generated can recognize human faces with accuracy of 87.05%. The system performs at its best if the person is around 150cm...
With the rise in traffic related crimes the need for an efficient automated surveillance system has become of utmost importance. This paper proposes a system to monitor video from traffic cameras and process it in real time for storing essential information of the vehicles in traffic. Histogram of Oriented Gradients (HOG) of extracted frames is used as features for classification (vehicle frame and...
In automation and standardization of quality of cane sugar in sugar factory, quantized identification process needs to be done. Identification of cane sugar was done based on image of cane sugar. In classification and identification based on image, colour models used could influence success rate of identification. This paper presents comparative study among RGB, HSV, HSI, YCbCr, and L∗a∗b colour models...
Digital visual media is one of the most commonly used means of communication. But, with the use of low-cost editing tools, tampering and counterfeiting visual contents are increasing enormously. In almost all the Image forensic application areas, the device used for capturing the image is of utmost importance as the origin of the particular image can act as a key evidence to substantiate the legitimacy...
Of late, traffic sign detection and recognition are becoming very prevalent topic as it enhances drivers towards safety and alert them with precaution information. This study reports about processing time of the individual color detection and recognition of the partial occlusion traffic sign that have been previously implemented using HSV and RGB color ratio and ANN and PCA method respectively for...
The general aim of this research is helping women to perform breast self-examination (BSE) for finding out any abnormality, change, or lump in the breasts. BSE involves checking the breasts for finding abnormalities, lumps, or changes. This paper reports about our initial efforts to detect and track the left and right breasts in real-time imaging. Image frames were processed considering the color...
Identification of minerals in petrographic thin sections using intelligent methods is very complex and challenging task which, mineralogists and computer scientists are faced with it. Textural features have very important role to identify minerals, and undoubtedly without using these features, recognition minerals in thin sections yield to many miss classification results. Thin sections have been...
This paper presents a color image classification method using rank based ensemble classifier. In this paper, we use color histogram in different color spaces and Gabor wavelet to extract color and texture features respectively. These features are classified by two classifiers: Nearest Neighbor (NN) and Multi Layer Perceptron (MLP). In the proposed approach, each set of features are classified by each...
As of now, unbounded solutions for efficient image recognition and retrieval have been proposed within various fields of computer science. Such solutions include both primitive and complex approaches to minimize the input required from the whole of the image to form the most accurate idea of the big picture. The proposed image recognizing agent accomplishes its task though the application of a scalable...
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