scholarly journals Linear Chromatic Adaptation Transform Based on Delaunay Triangulation

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Rok Kreslin ◽  
Pilar M. Calvo ◽  
Luis G. Corzo ◽  
Peter Peer
Keyword(s):  
Linear Model ◽  
Delaunay Triangulation ◽  
Color Constancy ◽  
Objective Evaluation ◽  
Input Image ◽  
Chromatic Adaptation ◽  
Color Information ◽  
Color Gamut ◽  
Color Constant ◽  
Better Than

Computer vision algorithms that use color information require color constant images to operate correctly. Color constancy of the images is usually achieved in two steps: first the illuminant is detected and then image is transformed with the chromatic adaptation transform (CAT). Existing CAT methods use a single transformation matrix for all the colors of the input image. The method proposed in this paper requires multiple corresponding color pairs between source and target illuminants given by patches of the Macbeth color checker. It uses Delaunay triangulation to divide the color gamut of the input image into small triangles. Each color of the input image is associated with the triangle containing the color point and transformed with a full linear model associated with the triangle. Full linear model is used because diagonal models are known to be inaccurate if channel color matching functions do not have narrow peaks. Objective evaluation showed that the proposed method outperforms existing CAT methods by more than 21%; that is, it performs statistically significantly better than other existing methods.

Evaluation of Luster, Hand Feel and Comfort Properties of Modified Polyester Woven Fabrics

2017 ◽  
Vol 12 (4) ◽  
pp. 155892501701200 ◽  
Author(s):  
Rong Zhou ◽  
Xueli Wang ◽  
Jianyong Yu ◽  
Zhenzhen Wei ◽  
Yu Gao
Keyword(s):  
Water Vapor ◽  
Evaluation System ◽  
Moisture Absorption ◽  
Water Vapor Permeability ◽  
Objective Evaluation ◽  
Cotton Fabrics ◽  
Woven Fabrics ◽  
Vapor Permeability ◽  
Pet Fabric ◽  
Better Than

This paper reports a hollow copolyester fiber modified with polyethylene glycol and sodium-5-sulfo-bis-(hydroxyethyl)-isophthalate, abbreviated as ECDP-H, which has the potential to be a replacement for cotton. The objective evaluation of luster (contrast glossiness) and Kawabata Evaluation System for Fabrics (KES-F) (four Primary Hand Parameters and the Total Hand) of ECDP-H, PET and cotton fabrics are studied in order to investigate the cotton-like appearance of the ECDP-H. The results of moisture regain and dynamic moisture absorption values obtained indicate that the hydrophilicity of the ECDP-H fabric is better than that of PET fabric. The thermo-physiological performance for three fabrics is determined using air and water vapor permeability, wicking, warm-cooling feeling, thermal resistance and vapor resistance. The results show that the ECDP-H fabric has better hand and comfort properties than cotton.

Partial Color Constancy of Isolated Surface Colors Examined by a Color-Naming Method

Perception ◽  
1989 ◽  
Vol 18 (1) ◽  
pp. 83-91 ◽  
Author(s):  
Keiji Uchikawa ◽  
Hiromi Uchikawa ◽  
Robert M Boynton
Keyword(s):  
Color Constancy ◽  
Color Naming ◽  
The State ◽  
Color Appearance ◽  
Chromatic Adaptation ◽  
Light Sources ◽  
Two Factors ◽  
The Subject ◽  
Spectral Distributions ◽  
Color Scales

Color samples selected from the OSA Uniform Color Scales set were viewed without any surround. Separate light sources were used to illuminate the samples and to control the state of adaptation of the subject, thereby separating two factors that are normally confounded. A color-naming procedure was used to assess shifts in color appearance produced by altering the spectral distributions of one or both light sources. The results confirm that chromatic adaptation, when it is the only factor operating, can mediate partial color constancy.

Chromatic adaptation and color constancy: A possible dichotomy

1986 ◽  
Vol 11 (3) ◽  
pp. 196-204 ◽  
Author(s):  
Michael H. Brill ◽  
Gerhard West
Keyword(s):  
Color Constancy ◽  
Chromatic Adaptation

Study on Reproduction of Color Information of Digital Image Based on Different Color Gamut

2012 ◽  
Vol 430-432 ◽  
pp. 838-841
Author(s):  
Wen Ge Chen
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Color Space ◽  
Mapping Method ◽  
Color Information ◽  
Color Gamut ◽  
Gamut Mapping ◽  
Processing Software ◽  
Image Processing Software ◽  
Different Color

This paper is based on digital image color information reproduction error in a different color gamut,Through the different color gamut mapping method, image processing software Photoshop is used to make experiment and to obtain the corresponding image effect. Using digital presses to print out and use Spectrodensitometer measure the corresponding data.Using Excel software for data processing and analysis, digital image color information of loss situation is obtained in RGB and CMYK color space, It can provide certain basis for control of the color loss.

Spectral Separation Method for Multi-Ink Printers Based on Color Constancy

2015 ◽  
Vol 731 ◽  
pp. 18-21
Author(s):  
Qiang Liu ◽  
Xiao Xia Wan ◽  
Zhen Liu ◽  
Peng Sun
Keyword(s):  
Color Constancy ◽  
Color Perception ◽  
Separation Method ◽  
Color Reproduction ◽  
Spectral Separation ◽  
Reproduction Performance ◽  
Color Constant ◽  
High Level ◽  
Constant Color

Color constancy is a key metric for evaluating the color reproduction performance. This contribution proposed a color constancy based spectral separation method for muti-ink printers from the prospect of color perception. Basing on our previously developped spectral printer modeling workflow, a novel color constancy based spectral separation method for muti-ink printers was proposed, which achieved high-level color-constant color reproduction.The experiment results shows that the workflow described in the paper not only could makes full use of device gamut, but also improves the comprehensive color constancy performance obviously. Averagely speaking, the Color Inconstancy Index of reproduced colors is reduced from 2.884 △E00 to 2.016 △E00 , while maintaining reasonable spectral and colorimetric reproduction accuracy.

scholarly journals Alternative Method for Estimating the Maintenance Cost of Roads in Anambra State, Nigeria

2020 ◽  
pp. 31-38
Author(s):  
Godspower Onyekachukwu Ekwueme ◽  
John Obatarhe Emunefe ◽  
Nkechi Udochukwu Otty ◽  
Charles Okechukwu Aronu
Keyword(s):  
Linear Model ◽  
Secondary Data ◽  
Quadratic Model ◽  
Maintenance Cost ◽  
Future Studies ◽  
Anambra State ◽  
Construction Company ◽  
Alternative Method ◽  
Proposed Model ◽  
Better Than

Aims: This study proposed an alternative method for the estimation of maintenance cost of roads in Anambra State, Nigeria. The proposed method referred to as the permuted quadratic model (PQM) involves permuting of the dependent variable of the quadratic model. Place and Duration of Study: The data used in this study was secondary data sourced from the records department of consolidated construction company asphalt plant Anambra state, Nigeria from 2004 to 2019. Methodology: The linear regression model and the permuted quadratic model were used to analyze the data for the study. Results: The result found that 74.0% correlation exists between the observed maintenance cost of roads and the predicted maintenance cost of roads using the linear model while the predicted maintenance cost of roads using the permuted quadratic model has 75.8% correlation with the observed maintenance cost of roads. This result indicates that the proposed permuted quadratic model performed better than the linear model for the estimation of the maintenance cost of roads in Anambra State. Conclusion: The study recommends the proposed model for the estimation of maintenance cost of roads in Anambra State until future studies prove otherwise.

scholarly journals A New Method for UAV Lidar Precision Testing Used for the Evaluation of an Affordable DJI ZENMUSE L1 Scanner

2021 ◽  
Vol 13 (23) ◽  
pp. 4811
Author(s):  
Rudolf Urban ◽  
Martin Štroner ◽  
Lenka Línková
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Point Cloud ◽  
Reference Points ◽  
New Method ◽  
Color Information ◽  
Dense Point ◽  
Aerial Vehicle ◽  
Systematic Shift ◽  
Precision Testing ◽  
Better Than

Lately, affordable unmanned aerial vehicle (UAV)-lidar systems have started to appear on the market, highlighting the need for methods facilitating proper verification of their accuracy. However, the dense point cloud produced by such systems makes the identification of individual points that could be used as reference points difficult. In this paper, we propose such a method utilizing accurately georeferenced targets covered with high-reflectivity foil, which can be easily extracted from the cloud; their centers can be determined and used for the calculation of the systematic shift of the lidar point cloud. Subsequently, the lidar point cloud is cleaned of such systematic shift and compared with a dense SfM point cloud, thus yielding the residual accuracy. We successfully applied this method to the evaluation of an affordable DJI ZENMUSE L1 scanner mounted on the UAV DJI Matrice 300 and found that the accuracies of this system (3.5 cm in all directions after removal of the global georeferencing error) are better than manufacturer-declared values (10/5 cm horizontal/vertical). However, evaluation of the color information revealed a relatively high (approx. 0.2 m) systematic shift.

scholarly journals CNN-Based Illumination Estimation with Semantic Information

2020 ◽  
Vol 10 (14) ◽  
pp. 4806 ◽  
Author(s):  
Ho-Hyoung Choi ◽  
Hyun-Soo Kang ◽  
Byoung-Ju Yun
Keyword(s):  
Neural Network ◽  
Computer Vision ◽  
Semantic Information ◽  
Color Constancy ◽  
Noisy Data ◽  
Image Data ◽  
Input Image ◽  
The Novel ◽  
Image Patches ◽  
Wide Range

For more than a decade, both academia and industry have focused attention on the computer vision and in particular the computational color constancy (CVCC). The CVCC is used as a fundamental preprocessing task in a wide range of computer vision applications. While our human visual system (HVS) has the innate ability to perceive constant surface colors of objects under varying illumination spectra, the computer vision is facing the color constancy challenge in nature. Accordingly, this article proposes novel convolutional neural network (CNN) architecture based on the residual neural network which consists of pre-activation, atrous or dilated convolution and batch normalization. The proposed network can automatically decide what to learn from input image data and how to pool without supervision. When receiving input image data, the proposed network crops each image into image patches prior to training. Once the network begins learning, local semantic information is automatically extracted from the image patches and fed to its novel pooling layer. As a result of the semantic pooling, a weighted map or a mask is generated. Simultaneously, the extracted information is estimated and combined to form global information during training. The use of the novel pooling layer enables the proposed network to distinguish between useful data and noisy data, and thus efficiently remove noisy data during learning and evaluating. The main contribution of the proposed network is taking CVCC to higher accuracy and efficiency by adopting the novel pooling method. The experimental results demonstrate that the proposed network outperforms its conventional counterparts in estimation accuracy.

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