A Graphic/Picture Classification Method Based on Spatial Characteristics of Colors

2012 ◽  
Vol 262 ◽  
pp. 31-35
Author(s):  
Sheng Yan Cai ◽  
Xuan Nie ◽  
Shu Qin Guo
Keyword(s):  
Discriminant Analysis ◽  
Classification Performance ◽  
Classification Method ◽  
Color Management ◽  
Essential Difference ◽  
Classification Rules ◽  
Color Reproduction ◽  
Color Distribution ◽  
Color Characteristics ◽  
Different Color

In order to get optimum color reproduction results on different color devices in color management, a proper rendering intent should be selected according to color characteristics of the image. In terms of differences on color characteristics, images could be classified into synthetic graphics and natural pictures. Different rendering intent should be applied on graphics and pictures. So graphic/picture automatic classification becomes a fundamental task of color management intellectualization. Characteristics on color distribution of a large number of images have been researched in our experiments. Then it is confirmed that the essential difference between graphic and picture is the characteristics on color distribution in the neighborhood of images rather than the number of colors or the volume of image gamut. Thus, the features which have distinct ability to show the differences could be used to build classification rules. In this paper, several mathematical features of image are extracted and selected by their classification performance. Based on these features, the discriminant analysis is adopted to build up discriminated functions. Finally, the accuracy of the functions has been tested and the precision is 96.75%.

IDT and Color Transfer-Based Color Calibration for Images Taken by Different Cameras

2020 ◽  
Vol 24 (1) ◽  
pp. 123-133
Author(s):  
Yoshiaki Ueda ◽  
Hideaki Misawa ◽  
Takanori Koga ◽  
Noriaki Suetake ◽  
Eiji Uchino ◽  
...  
Keyword(s):  
Calibration Method ◽  
Reference Image ◽  
Original Image ◽  
Color Reproduction ◽  
Color Transfer ◽  
Color Distribution ◽  
Color Calibration ◽  
Camera Parameters ◽  
Different Color ◽  
The Individual

Images of the same object taken by multiple different cameras should have the same color reproduction. However, the images sometimes show different color reproduction due to the individual differences of cameras or internal camera parameters automatically determined when the images are taken. Conventional color transfer methods can be used for unifying the color reproduction of images by transforming the color distribution of an image to that of a reference image. However, conventional methods do not always lead to a good color reproduction and sometimes result in the loss of color impression of original images. In the present paper, we propose a color calibration method for images of the same object taken by different cameras. Two color transfer methods are combined to realize color calibration without the loss of color impression of an original image. Resultant images obtained by the color transfer methods are appropriately mixed into an output image. In experiments, the proposed method is applied to a variety of images and the effectiveness of the proposed method is confirmed by subjective and objective evaluations.

scholarly journals Investigation of Color Reproduction on Linen Fabrics when Printing with Mimaki TX400-1800D Inkjet with Pigment TP250 Dyes

Coatings ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 354
Author(s):  
Tim Tofan ◽  
Rimantas Stonkus ◽  
Raimondas Jasevičius
Keyword(s):  
Mechanical Properties ◽  
Color Reproduction ◽  
Related Effect ◽  
Color Characteristics ◽  
Fabric Density ◽  
Different Types ◽  
The Difference ◽  
Printing Parameters ◽  
Linen Fabric

The aim of this research is to investigate related effect of dyeability to linen textiles related to different printing parameters. The study investigated the change in color characteristics when printing on linen fabrics with an inkjet MIMAKI Tx400-1800D printer with pigmented TP 250 inks. The dependence of color reproduction on linen fabrics on the number of print head passes, number of ink layers to be coated, linen fabric density, and different types of linen fabric was investigated. All this affects the quality of print and its mechanical properties. The change in color characteristics on different types of linen fabrics was determined experimentally. We determine at which print settings the most accurate color reproduction can be achieved on different linen fabrics. The difference between the highest and the lowest possible number of head passages was investigated. The possibilities of reproducing different linen fabric colors were determined.

Comparative Experiment of Color Reproduction Methods

2014 ◽  
Vol 1051 ◽  
pp. 967-970
Author(s):  
Qi Jia ◽  
Xu Liang Lv ◽  
Wei Dong Xu ◽  
Jiang Hua Hu ◽  
Xian Hui Rong
Keyword(s):  
Polynomial Regression ◽  
Rapid Development ◽  
Color Space ◽  
Digital Camera ◽  
Color Difference ◽  
High Tech ◽  
Comparative Experiment ◽  
Color Reproduction ◽  
Different Color ◽  
Time Image

Digital camera which has the advantage of real-time image transferring and easily processing is more and more widely used in the packaging and printing industry with the rapid development of high-tech electronics industry. However, the color in digital camera is not accurate which affect the application. To minimize the color difference between the color in the digital camera and the real color, the color reproduction methods is developing. The field comparative experiment is carried out to compare the performance of color reproduction methods, such as polynomial regression algorithm in different color space, and color checker passport. The results show that fourth order polynomial regression color reproduction in XYZ color space has the best performance.

scholarly journals Developing Support Vector Machine with New Fuzzy Selection for the Infringement of a Patent Rights Problem

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1263
Author(s):  
Chih-Yao Chang ◽  
Kuo-Ping Lin
Keyword(s):  
Support Vector Machine ◽  
Data Quality ◽  
Classification Performance ◽  
Patent Infringement ◽  
Classification Method ◽  
Training Dataset ◽  
Support Vector ◽  
Classification Problems ◽  
Data Quality Management ◽  
Patent Rights

Classification problems are very important issues in real enterprises. In the patent infringement issue, accurate classification could help enterprises to understand court decisions to avoid patent infringement. However, the general classification method does not perform well in the patent infringement problem because there are too many complex variables. Therefore, this study attempts to develop a classification method, the support vector machine with new fuzzy selection (SVMFS), to judge the infringement of patent rights. The raw data are divided into training and testing sets. However, the data quality of the training set is not easy to evaluate. Effective data quality management requires a structural core that can support data operations. This study adopts new fuzzy selection based on membership values, which are generated from fuzzy c-means clustering, to select appropriate data to enhance the classification performance of the support vector machine (SVM). An empirical example based on the SVMFS shows that the proposed SVMFS can obtain a superior accuracy rate. Moreover, the new fuzzy selection also verifies that it can effectively select the training dataset.

scholarly journals Ammonium nitrate regulated the color characteristic changes of pigments in Monascus purpureus M9

AMB Express ◽  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Di Chen ◽  
Yurong Wang ◽  
Mianhua Chen ◽  
Pei Fan ◽  
Guiling Li ◽  
...  
Keyword(s):  
Ammonium Nitrate ◽  
Food Industry ◽  
Ph Value ◽  
Extracellular Polysaccharide ◽  
Monascus Purpureus ◽  
Polysaccharide Biosynthesis ◽  
Real Time Quantitative Pcr ◽  
Color Characteristics ◽  
Different Color ◽  
Yellow Pigments

AbstractMonascus pigments (MPs) with different color characteristics, produced by submerged fermentation of Monascus purpureus M9, have potential application in food industry. In the present study, the effects and regulatory mechanisms of ammonium nitrate (AN) on the color characteristics of MPs were investigated. The concentration of intracellular pigments was significantly decreased when subjected to AN. The hue and lightness value indicated AN altered the total pigments appearance from original red to orange. The HPLC analysis for six major components of MPs showed that the production of rubropunctatin or monascorubrin, was significantly reduced to the undetectable level, whereas the yields of monascin, ankaflavin, rubropunctamine and monascorubramine, were apparently increased with AN supplement. To be noted, via real-time quantitative PCR strategy, the expression level of mppG, closely relative to orange pigments biosynthesis, was significantly down-regulated. However, the expression of mppE, involved in yellow pigments pathway, was up-regulated. Moreover, the broth pH value was dropped to 2.5–3.5 in the fermentation process resulted from AN treatment, along with the increased extracellular polysaccharide biosynthesis. Taken together, the change of MPs categories and amounts by AN might be the driving force for the color characteristics variation in M. purpureus M9. The present study provided useful data for producing MPs with different compositions and modified color characteristics.

scholarly journals A Complete Subspace Analysis of Linear Discriminant Analysis and Its Robust Implementation

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Zhicheng Lu ◽  
Zhizheng Liang
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Null Space ◽  
Small Sample Size ◽  
Classification Performance ◽  
Optimization Criterion ◽  
Small Sample ◽  
Scatter Matrix ◽  
Linear Discriminant ◽  
Maximum Margin Criterion

Linear discriminant analysis has been widely studied in data mining and pattern recognition. However, when performing the eigen-decomposition on the matrix pair (within-class scatter matrix and between-class scatter matrix) in some cases, one can find that there exist some degenerated eigenvalues, thereby resulting in indistinguishability of information from the eigen-subspace corresponding to some degenerated eigenvalue. In order to address this problem, we revisit linear discriminant analysis in this paper and propose a stable and effective algorithm for linear discriminant analysis in terms of an optimization criterion. By discussing the properties of the optimization criterion, we find that the eigenvectors in some eigen-subspaces may be indistinguishable if the degenerated eigenvalue occurs. Inspired from the idea of the maximum margin criterion (MMC), we embed MMC into the eigen-subspace corresponding to the degenerated eigenvalue to exploit discriminability of the eigenvectors in the eigen-subspace. Since the proposed algorithm can deal with the degenerated case of eigenvalues, it not only handles the small-sample-size problem but also enables us to select projection vectors from the null space of the between-class scatter matrix. Extensive experiments on several face images and microarray data sets are conducted to evaluate the proposed algorithm in terms of the classification performance, and experimental results show that our method has smaller standard deviations than other methods in most cases.

scholarly journals ANALYSIS OF WAYS OF SOLVING THE SEGMENTATION PROBLEM FOR HIGHLY TEXTURED OBJECTS

2019 ◽  
pp. 27-40
Author(s):  
S. I. Berezina ◽  
Yu. O. Gordienko ◽  
O. I. Solonets
Keyword(s):  
Fractal Dimension ◽  
Unit Area ◽  
Residential Areas ◽  
Color Characteristics ◽  
Analysis Window ◽  
Automated Processing ◽  
Interpretation Process ◽  
Different Color ◽  
Images Processing ◽  
Segmentation Problem

Increment of speed and reliability of aerospace images processing is directly related to solution of the task of automation of images interpretation process, which is achieved by minimizing search areas, detecting masked objects and defining the dynamics of changes in surveillance areas. The primary stage that in general determines the quality of results received by automated processing and interpretation is thematic segmentation of the image. In the process of thematic segmentation it is necessary to take into account presence of a large number of textured objects. The paper analyzes the ways of solving the segmentation problem for highly textured objects with large range of variation of possible color values. The research included separation of woodlands and single plants from meadows, steppes, etc., which are characterized by similar color characteristics, but differ in texture. It also included separation of residential areas from forests, which are characterized by the same grain size of texture and different color characteristics. The method of texture description, which is based on calculation of the number of differences in brightness per unit area of the image, the method of description and measurement of texture, characterized by the length of the series, the methods of texture description based on calculation of their fractal dimension have been investigated. In order to describe the texture by different methods, first of all, an aperture of the analysis window was defined. That aperture ensures separation of different classes of objects. The analyzed methods of texture description showed that areas of false identification are always present in the result images. It was determined that the best results were obtained with two of the discussed methods. The first one was the method of texture description and measurement based on calculation of the number of brightness differences per unit area of the image. The second one was the method of texture description based on calculation of fractal dimension by searching the area of the pyramid which covers image fragments. To obtain a more accurate segmented map of an image containing highly textured fragments, a combination of the two methods is suggested.

scholarly journals Aircraft Target Classification Method for Conventional Narrowband Radar Based on Micro-Doppler Effect

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Saiqiang Xia ◽  
Chaowei Zhang ◽  
Wanyong Cai ◽  
Jun Yang ◽  
Liangfa Hua ◽  
...  
Keyword(s):  
Doppler Effect ◽  
Classification Problem ◽  
Classification Performance ◽  
Central Moment ◽  
Classification Method ◽  
Support Vector ◽  
Machine Model ◽  
Different Types ◽  
Characteristics Analysis ◽  
The Time Domain

For a conventional narrowband radar system, its insufficient bandwidth usually leads to the lack of detectable information of the target, and it is difficult for the radar to classify the target types, such as rotor helicopter, propeller aircraft, and jet aircraft. To address the classification problem of three different types of aircraft target, a joint multifeature classification method based on the micro-Doppler effect in the echo caused by the target micromotion is proposed in this paper. Through the characteristics analysis of the target simulation echoes obtained from the target scattering point model, four features with obvious distinguishability are extracted from the time domain and frequency domain, respectively, that is, flicker interval, fractal dimension, modulation bandwidth, and second central moment. Then, a support vector machine model will be applied to the classification of the three different types of aircraft. Compared with the conventional method, the proposed method has better classification performance and can significantly improve the classification probability of aircraft target. The simulations are carried out to validate the effectiveness of the proposed method.

scholarly journals Local Non Zero Eigen Value Preservation Based Expression Recognition

2020 ◽  
Vol 8 (6) ◽  
pp. 3823-3832
Keyword(s):  
Discriminant Analysis ◽  
Feature Vector ◽  
Feature Fusion ◽  
Recognition Rate ◽  
Fusion Rule ◽  
Classification Performance ◽  
Support Vector ◽  
Expression Recognition ◽  
Fisher Discriminant Analysis ◽  
Fisher Discriminant

This work proposes an finest mapping from features space to inherited space using kernel locality non zero eigen values protecting Fisher discriminant analysis subspace approach. This approach is designed by cascading analytical and non-inherited face texture features. Both Gabor magnitude feature vector (GMFV) and phase feature vector (GPFV) are independently accessed. Feature fusion is carried out by cascading geometrical distance feature vector (GDFV) with Gabor magnitude and phase vectors. Feature fusion dataset space is converted into short dimensional inherited space by kernel locality protecting Fisher discriminant analysis method and projected space is normalized by suitable normalization technique to prevent dissimilarity between scores. Final scores of projected domains are fused using greatest fusion rule. Expressions are classified using Euclidean distance matching and support vector machine radial basis function kernel classifier. An experimental outcome emphasizes that the proposed approach is efficient for dimension reduction, competent recognition and classification. Performance of proposed approach is deliberated in comparison with connected subspace approaches. The finest average recognition rate achieves 97.61% for JAFFE and 81.48% YALE database respectively.

Sign in / Sign up

Export Citation Format

Share Document