Image matching algorithm based on SIFT using color and exposure information

Image matching based on scale invariant feature transform（SIFT） is one of the most popular image matching algorithms, which exhibits high robustness and accuracy. Grayscale images rather than color images are generally used to get SIFT descriptors in order to reduce the complexity. The regions which have a similar grayscale level but different hues tend to produce wrong matching results in this case. Therefore, the loss of color information may result in decreasing of matching ratio. An image matching algorithm based on SIFT is proposed, which adds a color offset and an exposure offset when converting color images to grayscale images in order to enhance the matching ratio. Experimental results show that the proposed algorithm can effectively differentiate the regions with different colors but the similar grayscale level, and increase the matching ratio of image matching based on SIFT. Furthermore, it does not introduce much complexity than the traditional SIFT.

Color Matching of Pre-colored Fiber Blends Based on Two-Constant Kubelka-Munk Theory

Some modifications of two-constant Kubelka-Munk theory has been made for the color matching of pre-colored fiber blends. The scattering coefficients of three primaries are averaged and taken as initial coefficients in each wavelength. The unit sums of concentration in E-Allen’s Algorithm were removed in the case of pre-colored fiber blends. Predicted blend ratios and reflectance curves agree very well with measured ones and color differences are within the tolerant limit, showing satisfactory matching results.

The Three-region Method of Color Matching in the Presence of Fluorescent Whitening Agents

An expression of reflectance of fluorescent dyes in emission region was used in this article. Through the analysis of the spectral radiance factor of fluorescent whitening agents(FWA), the color matching of FWA was studied and the three-region method of color matching method was put forward. The method was proved to be reliable for the dyes used and was easy to apply for the color matching of FWAs.

Color Matching for Fiber Blends Based on Stearns-Noechel Model

Prediction of the formula for matching a given color standard by blending pro-dyed fibers is of considerable importance to the textile industry. This kind of formulation suffers from a lack of computer-aided tool to assist the colorist attempting to find a good recipe to reproduce a target color. In this article a tristimulus color matching algorithm based on Stcarns-Noechel model is proposed. This algorithm was run to predict recipes for 36 viscose blends. The maximum color difference is 0.97 CIELAB units. It is demonstrated that the algorithm can be used in color matching of fiber blends.

Smart Clothing Fabric Color Matching with Reference to Popular Colors

Color economy and market fashion trend have an increasing impact on clothing fabric color matching.Therefore,a smart clothing fabric color matching system with reference to popular colors is designed to realize the diversification of clothing color matching,which includes a palette generation module and a clothing fabrics-palette color matching network(CF-PCN).Firstly,palette generation module generates palettes referring popular colors while maintains color styles of clothing fabrics.Secondly,CF-PCN generates color matching images containing color information of palettes.The experimental results show that the color matching system has a higher average pixel ratio of palette colors and contains more palette color information.It demonstrates that the system achieves color matching innovation referring popular colors while retaining color style of clothing brands and provides designers with appropriate color matching solutions.

A Four-color Matching Method Combining Neural Networks with Genetic Algorithm

A brief review of color matching technology and its application of printing RGB images by CMY or CMYK ink jet printers is presented, followed by an explanation to the conventional approaches that are commonly used in color matching. Then, a four color matching method combining neural network with genetic algorithm is proposed. The initial weights and thresholds of the BP neural network for RGB to CMY color conversion are optimized by the new genetic algorithm based on evolutionarily stable strategy. The fourth component K is generated by using GCR (Gray Component Replacement) concept. Simulation experiments show that it is well behaved in both accuracy and generalization performance.

3D human face reconstruction based on band-limited binary patterns

Face recognition technology has great prospects for practical applications. Three-dimensional（3D） human faces are becoming more and more important in consideration of the limits of two-dimensional face recognition. We propose an active binocular setup to obtain a 3D colorful human face using the band-limited binary patterns（BBLP） method. Two grayscale cameras capture the BBLP projected onto the target of human face by a digital light processing（DLP） projector synchronously. Then, a color camera captures a colorful image of the human face. The benefit of this system is that the 3D colorful human face can be obtained easily with an improved temporal correlation algorithm and the precalibration results between three cameras. The experimental results demonstrated the robustness, easy operation, and the high speed of this 3D imaging setup.

Novel metal-dielectric metameric optical filters for optical security devices

Optical security devices play an essential role in the fight against counterfeiting. In this paper, we study and design a pair of metal-dielectric optical filters based on metameric effect, which offer a hidden image effect by the color shift at a specific angle of observation. Compared with all-dielectric multilayer system, the metal-dielectric multilayer structure has larger color shift with varying incident angle, higher color saturation and fewer layers. Finally, the stacks with 5 layers and 7 layers are achieved, and the color difference index is only 0.71, which shows good metameric matching effect. Simultaneously, the sensitivity of filters to deposition errors is analyzed when the thickness deviation is ±2%, and the results show that the two filters have good manufacturability.