Abstract: A method of visualizing a color deviation of an actual color on a vehicle panel being painted utilizing a computer. A reference color image is displayed on a monitor to confirm that the reference color image is the appropriate color image relating to the actual color. Differences between that displayed reference color image and the actual color are inputted into the computer and the reference image is then translated into a revised color image. The revised color image is displayed on the monitor along with the reference color image such that a user can visually compare the differences between that displayed reference color image and displayed revised color image. The displayed revised color image can then be compared to the actual color to determine if any color deviations between the revised color image and the actual color remain.

Abstract: A system and method of determining a paint formula having an effect pigment is provided. The system includes a coarseness gauge which may be placed adjacent to a painted surface, such as that of a vehicle. A technician compares the gauge to the painted surface to determine a coarseness of the effect pigment. This coarseness is then used to select and/or adjust a paint formula such that an accurate match may be achieved.

Abstract: A method for determining if a proposed color solution, such as paint, pigments, or dye formulations, is acceptable, is provided. The inputs to the system are the actual color values of an item, differential color values, a proposed color solution, and second color values associated with the proposed color solution. The system includes an artificial intelligence model to analyze the inputs and produce an output for communicating whether the proposed color solution is acceptable. The artificial intelligence model may be embodied in a neural network.

Abstract: A computer based system and method provides color solutions to a customer. A solution request from an operator located at a remote location is received and delivered to a central location over a computer network. A composite solution database is searched to determine a color solution as a function of the solution request.

Abstract: A system and method for converting a color formula from compositions such as paints, pigments, or dye formulations, is provided. The input to the system is a first color formula. The system includes an input device for entering a plurality of color formula values and an artificial intelligence conversion model coupled to the input device. The conversion model produces an output signal for communicating a second color formula. The artificial intelligence model may be embodied in a neural network. More specifically, the conversion model may be a back propagation neural network.

Abstract: A computer based system and method provides color solutions to a customer over a computer network. A solution request is received from an operator. A composite solution database is searched to determine a color solution as a function of the solution request.

Abstract: A system and method for organizing a plurality of sets color values into a plurality of color groups, such as paint, pigments, or dye formulations, is provided. The inputs to the system are the color values of a proposed paint, dye or colorant formulation and color measurement angles. The system includes an input device for entering a plurality of sets of color values and an artificial intelligence cluster model coupled to the input device. The cluster model produces an output signal indicative of the one color group to which a set of color values belongs. The artificial intelligence model may be embodied in a neural network. More specifically, the cluster model may be a self-organizing map neural network.

Abstract: A method and apparatus for color matching are provided, in which paint recipe neural networks are utilized. The color of a standard is expressed as color values. The neural network includes an input layer having nodes for receiving input data related to paint bases. Weighted connections connect to the nodes of the input layer and have coefficients for weighting the input data. An output layer having nodes are either directly or indirectly connected to the weighted connections and generates output data related to color values. The data to the input layer and the data from the output layer are interrelated through the neural network's nonlinear relationship. The paint color matching neural network can be used for, but not limited to, color formula correction, matching from scratch, effect pigment identification, selection of targets for color tools, searching existing formulas for the closest match, identification of formula mistakes, development of color tolerances and enhancing conversion routines.

Abstract: The invention provides a coating composition for use with metallic substrates that provides desirable levels of adhesion to metal, sandability without the production of harmful dust, corrosion resistance, and recoatability. The coating composition of the invention comprises a polyurethane film-forming component, and a corrosion protection component present in the composition in an amount effective in minimizing corrosion and adhesion loss of the coating at the substrate. A cured film of the coating applied to metallic substrates, previously coated substrates, as well as plastic substrates has improved corrosion resistance following Salt Spray Cabinet exposure.

Abstract: A method and apparatus for color matching are provided, in which paint recipe neural networks are utilized. The color of a standard is expressed as color values. The neural network includes an input layer having nodes for receiving input data related to paint bases. Weighted connections connect to the nodes of the input layer and have coefficients for weighting the input data. An output layer having nodes are either directly or indirectly connected to the weighted connections and generates output data related to color values. The data to the input layer and the data from the output layer are interrelated through the neural network's nonlinear relationship. The paint color matching neural network can be used for, but not limited to, color formula correction, matching from scratch, effect pigment identification, selection of targets for color tools, searching existing formulas for the closest match, identification of formula mistakes, development of color tolerances and enhancing conversion routines.

Abstract: A method and apparatus for color matching are provided, in which paint recipe neural networks are utilized. The color of a standard is expressed as color values. The neural network includes an input layer having nodes for receiving input data related to paint bases. Weighted connections connect to the nodes of the input layer and have coefficients for weighting the input data. An output layer having nodes are either directly or indirectly connected to the weighted connections and generates output data related to color values. The data to the input layer and the data from the output layer are interrelated through the neural network's nonlinear relationship. The paint color matching neural network can be used for, but not limited to, color formula correction, matching from scratch, effect pigment identification, selection of targets for color tools, searching existing formulas for the closest match, identification of formula mistakes, development of color tolerances and enhancing conversion routines.

Abstract: A computer based system and method provides color solutions to a customer over a computer network. A solution request is received from an operator. A composite solution database is searched to determine a color solution as a function of the solution request.

Abstract: A system and method for organizing a plurality of sets color values into a plurality of color groups, such as paint, pigments, or dye formulations, is provided. The inputs to the system are the color values of a proposed paint, dye or colorant formulation and color measurement angles. The system includes an input device for entering a plurality of sets of color values and an artificial intelligence cluster model coupled to the input device. The cluster model produces an output signal indicative of the one color group to which a set of color values belongs. The artificial intelligence model may be embodied in a neural network. More specifically, the cluster model may be a self-organizing map neural network.

Abstract: A system and method for converting a color formula from compositions such as paints, pigments, or dye formulations, is provided. The input to the system is a first color formula. The system includes an input device for entering a plurality of color formula values and an artificial intelligence conversion model coupled to the input device. The conversion model produces an output signal for communicating a second color formula. The artificial intelligence model may be embodied in a neural network. More specifically, the conversion model may be a back propagation neural network.

Abstract: A computer based system and method provides color solutions to a customer. A solution request from an operator located at a remote location is received and delivered to a central location over a computer network. A composite solution database is searched to determine a color solution as a function of the solution request.

Abstract: system and method for determining if a proposed color solution, such as paint, pigments, or dye formulations, is acceptable, is provided. The inputs to the system are the color values of a proposed paint or other color formulation and differential color values. The system includes an input device for entering a proposed color solution and an artificial intelligence tolerance model coupled to the input device. The tolerance model produces an output signal for communicating whether the proposed color solution is acceptable. The artificial intelligence model may be embodied in a neural network. More specifically, the tolerance model may be a back propagation neural network.

Abstract: A method and apparatus for color matching are provided, in which paint recipe neural networks are utilized. The color of a standard is expressed as color values. The neural network includes an input layer having nodes for receiving input data related to paint bases. Weighted connections connect to the nodes of the input layer and have coefficients for weighting the input data. An output layer having nodes are either directly or indirectly connected to the weighted connections and generates output data related to color values. The data to the input layer and the data from the output layer are interrelated through the neural network's nonlinear relationship. The paint color matching neural network can be used for, but not limited to, color formula correction, matching from scratch, effect pigment identification, selection of targets for color tools, searching existing formulas for the closest match, identification of formula mistakes, development of color tolerances and enhancing conversion routines.

Abstract: There is disclosed a metallic and nonmettalic water borne base coat compositions exhibiting excellent appearance. A method for long term stability and the introduction of aluminum flake pigments into a water borne coating is also disclosed. The method is based on storing the aluminum flake in a solvent environment with introduction of the aluminum flake in to the aqueous environment just before applying the base coat coating. A water reducible acrylic resin with nonionic and acid functionality has been disclosed that allows for direct introduction of aluminum flake in to an aqueous environment. The coating vehicle is based on acrylic latex vehicle which exhibits excellent drying and film properties. The rheology control agent employed allows for a drier application of the coating to the substrate. The coating compositions disclosed are also in compliance with current and proposed volatile organic compound regulations.