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This paper examines the application of a deep learning approach to converting night-time images to day-time images. In particular, we show that a convolutional neural network enables the simulation of artificial and ambient light on images. In this paper, we illustrate the design of the deep neural network and some preliminary results on a real indoor environment and two virtual environments rendered...
Someone who does not have vocal cords, has no ability to produce voice and speech. This problem is suffered by laryngectomy patients. Over half of all laryngectomy patients worldwide are using electrolarynx for the rehabilitation of their speech ability. Unfortunately, the electrolarynx is relatively expensive, especially for patient from the lower classes. In this research, portable speech aid tool...
In this paper, artificial neural network (ANN) and improved binary gravitational search algorithm (IBGSA) are utilized to detect objects in images. Watershed algorithm is used to segment images and extract the objects. Color, texture and geometric features are extracted from each object. IBGSA is used as a feature selection method to find the best subset of features for classifying the desired objects...
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...
Fast and robust traffic sign recognition is very important but difficult for the safety driving assist systems. This study addresses the fast and robust traffic sign recognition to enhance safety driving. We first adopt the typical Hough transform methods to implement coarse-grained locating of the candidate regions (shapes of rectangle, triangle and circle, etc.) of the traffic signs; and then propose...
Camera-based computer vision technology is able to assist visually impaired people to automatically recognize banknotes. A good banknote recognition algorithm for blind or visually impaired people should have the following features: 1) 100% accuracy, and 2) robustness to various conditions in different environments and occlusions. Most existing algorithms of banknote recognition are limited to work...
Recently, accidents such that seniors fall down from the bed in care facilities or hospitals are increased. To prevent these accidents, we have developed the awakening behavior detection system using Neural Network. In this paper, it is a problem that the detection success rate of the current system using captured image in the clinical site is not enough. So, we analyze the captured image in the clinical...
Paper currency recognition with good accuracy and high processing speed has great importance for banking system. How to extract high quality monetary features from currency images is a key problem in paper currency recognition. Based on the traditional local binary pattern (LBP) method, an improved LBP algorithm, called block-LBP algorithm, is proposed in this paper for characteristic extraction....
A facial recognition based verification system is a computer application for automatically identifying or verifying a person from a digital image or a video feature [1]. Our work deals with the recognition of human faces. One stage of recognizing a face is to figure out how the eyes, nose and mouth are placed in the facial structure which are used as decision support entities of the system configured...
This paper presents a monocular vision-based preceding vehicle detection system using Histogram of Oriented Gradient (HOG) based method and linear SVM classification. Our detection algorithm consists of three main components: HOG feature extraction, linear SVM classifier training and vehicles detection. Integral Image method is adopted to improve the HOG computational efficiency, and hard examples...
Illumination and expression variation are the major challenges in the face recognition. This paper presents comparative analysis of two normalization techniques namely, DCT in Log domain and 2-point normalization method.. The DCT is employed to compensate for illumination variations in the logarithm domain. Since illumination variation lies mainly in the low frequency band, an appropriate number of...
A machine vision based tinplate surface inspection system was developed. The system was composed of two parallel line scan CCD cameras, a special designed wide field illumination, which can overcome the vibration of tinplate, and a software based on SOM (Self-Organizing Feature Map) neural network. The images of tinplate were captured by cameras. All kinds of defects candidates such as pinholes, scallops,...
Patch-based face recognition is a robust method which aims to tackle illumination changes, pose changes and partial occlusion at the same time. In this paper, we analyzed the effects of different dimension reduction and normalization techniques for patch-based face recognition. Apart from previously used dimension reduction methods such as DCT and PCA, we have applied NPCA and NNDA at the feature...
Current E-commerce technologies cannot provide enough individual information to buyers. Augmented Reality (AR) technology might improve the performance of E-commerce by overlaying virtual information of products on the real world. But usual tracking technology based on markers is impeding the application of AR technology in business. This paper proposes an approach to feature point correspondence...
In this paper we propose a novel approach to constructing a discriminant visual codebook in a simple and extremely fast way as a one-pass, that we call Resource-Allocating Codebook (RAC), inspired by the Resource Allocating Network (RAN) algorithms developed in the artificial neural networks literature. Unlike density preserving clustering, this approach retains data spread out more widely in the...
Feature extraction is one of the important tasks in face recognition. Structural and statistical based approaches are two broad categories of feature extraction. This paper proposes a statistical approach for feature extraction based on Generalized Pseudo-Zernike Moment (GPZM) invariants which is powerful to characterize the image using region based shape features and also invariant to size, tilt,...
The control over electronic system using hand gestures is an innovative user interface that resolves the complications of using numerous remote controls for appliances. Founded on a unified set of hand gestures, this system interprets the user's hand gestures into pre-specified commands to control one or many devices simultaneously. However, of late, security has been of major concern among the people...
The project of developing an intelligent Chinese chess playing robot in natural environment is facing many challenges in which a robust illumination invariant recognition of the Chinese printed character in a chess piece is addressed in this paper. Instead of illumination sensitive image binarization which inevitably causes information loss and even tends to fail recognition, the proposed approach...
In this paper, a novel method is proposed for face recognition based on pulse coupled neural network (PCNN) time signature. In this approach, a probe face is first extracted PCNN time signature as the recognition features, which a two-dimensional image is projected to a low one-dimensional feature space and then is classified based on the known samples. An extensive experimental investigation is conducted...
The authors present a new algorithm for iris recognition. Segmentation is based on local statistics, and after segmentation, the image is subjected to contrast-limited, adaptive histogram equalization. Feature extraction is then conducted using two directional filters (vertically and horizontally oriented). The presence (or absence) of ridges and their dominant directions are determined, based on...
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