Performance evaluation of wavelet scattering network in image texture classification in various color spaces

The optimized color space is searched by using the wavelet scattering network in the KTH_TIPS_COL color image database for image texture classification. The effect of choosing the color space on the classification accuracy is investigated by converting red green blue （RGB） color space to various other color spaces. The results show that the classification performance generally changes to a large degree when performing color texture classification in various color spaces, and the opponent RGB-based wavelet scattering network outperforms other color spaces-based wavelet scattering networks. Considering that color spaces can be changed into each other, therefore, when dealing with the problem of color texture classification, converting other color spaces to the opponent RGB color space is recommended before performing the wavelet scattering network.

Low-dimensional multi-spectral space for color reproduction based on nonnegative constrained principal component analysis

In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.

Color Measurement of Segmented Printed Fabric Patterns in Lab Color Space from RGB Digital Images

Colors of textile materials are the first parameter of quality evaluated by consumers and a key component considered in selecting printed fabric. In the textiles industry, digital printed fabric analysis is one of the basic elements in successfully utilizing a color mechanism scheme and objectively evaluating fabric color alterations. Precise color measurement, however, is mostly used in sample analysis and quality inspection which help to produce reproducible or similar product. It is important that for quality inspection, the color of the product should be measured as a necessary requirement of quality control whether the product is to be accepted or not. Presented in this study is an unsupervised segmentation of printed fabrics patterns using mean shift algorithm and color measurements over the segmented regions of printed fabric patterns. The results established a consistent and reliable color measurement of multiple color patterns and appearance with the established range without any interactions.

Deer Body Adaptive Threshold Segmentation Algorithm Based on Color Space

In large-scale deer farming image analysis,K-means or maximum between-class variance(Otsu)algorithms can be used to distinguish the deer from the background.However,in an actual breeding environment,the barbed wire or chain-link fencing has a certain isolating effect on the deer which greatly interferes with the identification of the individual deer.Also,when the target and background grey values are similar,the multiple background targets cannot be completely separated.To better identify the posture and behaviour of deer in a deer shed,we used digital image processing to separate the deer from the background.To address the problems mentioned above,this paper proposes an adaptive threshold segmentation algorithm based on color space.First,the original image is pre-processed and optimized.On this basis,the data are enhanced and contrasted.Next,color space is used to extract the several backgrounds through various color channels,then the adaptive space segmentation of the extracted part of the color space is performed.Based on the segmentation effect of the traditional Otsu algorithm,we designed a comparative experiment that divided the four postures of turning,getting up,lying,and standing,and successfully separated multiple target deer from the background.Experimental results show that compared with K-means,Otsu and hue saturation value(HSV)+K-means,this method is better in performance and accuracy for adaptive segmentation of deer in artificial breeding scenes and can be used to separate artificially cultivated deer from their backgrounds.Both the subjective and objective aspects achieved good segmentation results.This article lays a foundation for the effective identification of abnormal behaviour in sika deer.

Color spaces of safflower (Carthamus tinctorius L.) for quality assessment

Objective:In this study,safflower(Carthamus tinctorius L.)was taken as a representative example to examine the application of color characteristics to evaluate quality.Methods:A computer vision system was established for the objective and nondestructive assessment of color using image processing algorithms.Color parameters were investigated based on the RGB,L*a*b and HSV color spaces.The content of hydroxysafflor yellow A(HSYA),a major bioactive constituent of safflower,was determined by high-performance liquid chromatography.The relationship between HSYA content and color values was investigated by Pearson correlation analysis.A multiple linear regression model was established to predict the HSYA content from color values.Results:The red color and lightness of safflower were found to be significantly related to HSYA content.The prediction equation obtained by multiple regression was reliable with an R2 value of 0.805(P<.01).Conclusion:The results suggest that the computer vision technique could be used as a promising and non-destructive technology for color measurement and quality evaluation of CHM.

Wide-Band Multi-spectral Space for Color Representation

This paper develops a wide-band multi-spectral space for color representationwith Aitken PCA algorithm. This novel mathematical space using the broad-band spectra matchingmethod aims at improving the accuracy of color representation as well as reducing costs forprocessing and storing multi-spectral images. The results show that the space can present ourexperimental original spectral spaces (i. e. Munsell color matt and DIN-6164 color chips) with highefficiency, and that the spanning space with three eigenvectors can present the original space atmore than 98% CSCR, and when 5 eigenvectors are used it can cover almost the whole o-riginal spaces.

A Study on the Influence of Luminance L* in the L*a*b* Color Space during Color Segmentation

In this paper an evaluation of the influence of luminance L* at the L*a*b* color space during color segmentation is presented. A comparative study is made between the behavior of segmentation in color images using only the Euclidean metric of a* and b* and an adaptive color similarity function defined as a product of Gaussian functions in a modified HSI color space. For the evaluation synthetic images were particularly designed to accurately assess the performance of the color segmentation. The testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. From the results is obtained that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume.

Automatic Defect Detection and Grading of Single-Color Fruits Using HSV （Hue, Saturation, Value） Color Space

Machine vision has been recently utilized for quality control of food and agricultural products, which was traditionally done by manual inspection. The present study was an attempt for automatic defect detection and sorting of some single-color fruits such as banana and plum. Fruit images were captured using a color digital camera with capturing direction of zero degree and under illuminant D65. It was observed that growing decay and time-aging made surface color changes in bruised parts of the object. 3D RGB and HSV color vectors as well as a single channel like H （hue）, S （saturation）, V （value） and grey scale images were applied for color quantization of the object. Results showed that there was a distinct threshold in the histogram of the S channel of images which can be applied to separate the object from its background. Moreover, the color change via the defect and time-aging is correctly distinguishable in the hue channel image. The effect of illumination, gloss and shadow of 3D image processing is less noticeable for hue data in comparison to saturation and value. The value of H channel was quantized to five groups based on the difference between each pixel value and the H value of a healthy object. The percentage of different degree of defects can be computed and used for grading the fruits.

Circle Detection Based on HSI Color Space

A method based on HSI color space is presented to solve the problem of circle detection from color images. In terms of the evaluation to the edge detection method based on intensity, the edge detection based on hue is chosen to process the color image, and the simplified calculation of hue transform is discussed. Then the algorithm of circle detection based on Canny edge detection is proposed. Due to the dispersive distribution of the detected result, Hough transformation and template smooth are used in circle detection, and the proposed method gives a quite good result.

Strategies for Applying LED Lights in Night Space Lighting for Bridges

LED lights have been widely used in urban night space lighting in recent years as they are small,energy-saving,and efficient.This article explores the use of LEDs in bridge night space lighting and their application strategies.The aim is to offer valuable insights and references for urban planners and bridge lighting designers in China.By advancing the application of LED technology in bridge night lighting,the goal is to enhance the city’s nighttime ambiance,making the bridge an iconic landmark and a defining feature of the city.

HB-Continuous Mappings in L-Topological Space

In this paper, we introduce and study the notion of HB-closed sets in L-topological space. Then, HB-convergence theory for L-molecular nets and L-ideals is established in terms of HB-closedness. Finally, we give a new definition of fuzzy H-continuous [1] which is called HB-continuity on the basis of the notion of H-bounded L-subsets in L-topological space. Then we give characterizations and properties by making use of HB-converges theory of L-molecular nets and L-ideals.

Modified Multispectral Space for Color Representation

Conventional multispectral space for color representation is modified by algorithm of cluster analysis and principal component analysis. Results show that the newer modified multispectral space not only keeping the structure of the original space but eliminating zero crosses as well its accuracy of color representation is higher than the conventional.

Energy-Saving Effect of Discolored Decorative Boards in Flexible Interior Space

Green,energy conservation and environmental protection have increasingly become the theme of the sustained and healthy development of cities against the background of new urbanization,which indicates that the problem of building energy consumption has received growing attention.This paper explores the impact of energy-saving decorations in flexible interior space on energy-saving effect of buildings so as to broaden the horizon of energy conservation in building,thereby alleviating the problem of energy shortage in China.

Space Color Design of Medical and Nursing Institutions Based on Adaptive Aging Characteristics

With the acceleration of China’s aging process and the rapid development of social economy,the government’s strong support for the integration of medical and nursing has made the construction of medical and nursing buildings more efficient.At the same time,the need for old-age care is more diversified and hierarchical,and the life cycle is more obvious.Designing an aging color environment for the elderly with different visual abilities in medical care buildings has become a problem for investors,operators and designers.This paper takes the indoor color of medical and nursing buildings as the research object,and combines the characteristics of the elderly’s visual acuity and the ratio and efficacy of indoor colors to investigate two high-end medical and nursing institutions in Beijing and Nanjing.Based on the physical,psychological and behavioral needs,this paper explores the appropriate aging color design method for the living space of the elderly in the medical institutions,aiming to make a meagre effort for the in-depth research and practice of indoor environment design of medical institutions in the future.

IAACS: Image aesthetic assessment through color composition and space formation

Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics of the general public. Although deep learning methods have successfully learned good visual features from images,correctly assessing the aesthetic quality of an image remains a challenge for deep learning. Methods To address this, we propose a novel multiview convolutional neural network to assess image aesthetics assessment through color composition and space formation(IAACS). Specifically, from different views of an image––including its key color components and their contributions, the image space formation, and the image itself––our network extracts the corresponding features through our proposed feature extraction module(FET) and the Image Net weight-based classification model. Result By fusing the extracted features, our network produces an accurate prediction score distribution for image aesthetics. The experimental results show that we have achieved superior performance.

Preliminary Study on the Mutagenic Effects of Space Flight on Alfalfa Seeds

[Objective] The study aimed to understand the mutagenic effects of space flight on alfalfa seeds.[Method] Seeds of three lines of alfalfa were carried into orbit by the satellite 'Shijian-8' for space fight,the indices including seed germination rate,plant height and growth rate,were measured after the seeds been retrieved.[Result] Remarkable mutagenic effects occurred on the flight seeds,which were mainly presented by abnormal cotyledon,extended variation range of plant height and growth rate.Nineteen plants with increased plant height were preliminarily screened from the T0 progenies,but whether the mutated trait could inherit should be confirmed in further study.Three flight lines of alfalfa are different in the percentages of abnormal cotyledon(10%-18%),variation range of plant height(increased 30%-150% compared to control),selected plant number with increased plant height(5-7 plants),suggesting that differences exits between the three lines in mutation efficiency.[Conclusion] Valuable mutated materials could be obtained by space flight and applied in modern agriculture.

Neural Network Method for Colorimetry Calibration of Video Cameras

To transfer the color data from a device (video camera) dependent color space into a device? independent color space, a multilayer feedforward network with the error backpropagation (BP) learning rule, was regarded as a nonlinear transformer realizing the mapping from the RGB color space to CIELAB color space. A variety of mapping accuracy were obtained with different network structures. BP neural networks can provide a satisfactory mapping accuracy in the field of color space transformation for video cameras.

New Color-Difference Formula Based on CIECAM97s

To deduce a new color difference formula based on CIE 1997 Color Appearance Model(CIECAM97s), a color space J a 1 b 1 is first constructed with color appearance descriptors J,a,b in CIECAM97s. The new formula is then deduced in the space and named CDF CIECAM97s. The factors for lightness, chroma and hue correction in the formula are derived by linear regression according to BFD? CP data sets. It is found by statistical analysis that CDF CIECAM97s is in closer accordance with the visual assessments when compared with CMC(1∶1), CIE94 and CIE L *a *b * color difference formulae. Based on color appearance model, the new color difference formula can be used to predict color difference perception in a varity of different viewing conditions.

Breeding of a Natural Colored-Cocoon Bombyx mori Variety Shuhuang No.1

[Objective] This study aimed to develop a new Bombyx mori variety Shuhuang No.1 and investigate its characteristics.[Method] The new variety was developed through cross breeding and pedigree separation.Its characteristics were identified by laboratory tests and rural promotion practices in Sichuan Province.[Result]The cocoon produced by the new variety Shuhuang No.1 was golden-yellow and radiantly beautiful.Shuhuang No.1 was strong and easy to rear,uniform in development.The male and female ones could be distinguished by their larval color and markings.The cocoon yield per 10 000 the 4th instar larvae reached 20.30 kg; the length of a cocoon filament was about 1 115.0 m,and a non-broken filament was 882.95 mm long,accounting for 79.15％ of the total length.The raw silk ratio of fresh cocoon was 18.39％,and the neatness was 91.25 point.The main economic features of Shuhuang No.1 were better than those of the control.[Conclusion] The new variety had been approved by Sichuan Silkworm Evaluation Commission.It can be promoted in parent silkworm rearing areas Sichuan,Chongqing,Yangtze River basin.

Study on SSR Markers Linked to Flesh Color around the Stone of Prunus persica(L.) Batsch

[Objective] This study aimed to select SSR molecular markers linked to flesh color around the stone of Prunus persica （L.） Batsch. [Method] P. persica （L.） Batsch varieties Chongyanghong and Yanhong were used as parents to construct F1 orthogonal group. A total of 138 FI individuals were selected as experimental materi- als for construction of color around the stone gene pool （B1） and non-color around the stone gene pool （B2） by using bulked segregant analysis （BSA） method, molec- ular markers linked to the flesh color around the stone of P. persica （L.） Batsch were selected with SSR molecular marker technology. [Result] After selection with 256 pairs of SSR primers, three pairs of molecular markers linked to the gene con- trolling flesh color around the stone of P. persica （L.） Batsch were selected （UDP96- 003, ch04g09 and UDP97-402）. In addition, genetic distances between the three molecular markers and the gene controlling flesh color around the stone of P. persi- ca （L.） Batsch were calculated, which were 16.7, 10.1 and 17.0 cM, respectively. [Conclusion] This study laid the foundation for further selection of co-dominant molecular markers with closer genetic distance.