Method and apparatus for adaptive color scanning/printing data correction employing neural networks
First Claim
1. A method for adaptive color scanning/printing data correction, wherein a color scanning/printing system includes a color image inputting device, a neural network, and a color image outputting device, said inputting device being connected to said neural network, and said neural network being connected to said outputting device, said method comprising the steps of:
- providing pre-selected test color image patterns to said color image outputting device for outputting a first output image;
inputting said first output image to said inputting device to obtain color data of said first output image, and processing a learning sample generated with said color data by said neural network;
said neural network subsequently taking the average of the data values of all the color picture elements within a neighborhood in the predetermined vicinity of each input color picture element, and taking the average data value of all the color picture elements within the corresponding neighborhood of the corresponding output color picture element, so as to constitute a learning sample pair including the averaged color data values of input and output gamuts respectively; and
said neural network processing said generated learning sample pair to perform a neural network learning procedure.
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Abstract
A method and apparatus for adaptive color scanning/printing data correction to effectively adjust to an arbitrary combination of color image scanning input and printing output devices for reproducing color image at optimized resemblance. An improved back propagation algorithm is employed to reduce the learning error and accelerate the process of learning procedure by increasing the rate of convergence. A method of characteristics extracting functionalization is utilized to urge the successful convergence of the learning procedure of the neural network, and reduce the color discrepancy and accelerate the process of learning convergence. An enhanced grey-scale balancing scheme is also utilized to extract the grey component of a learning sample under a predetermined condition and re fetch again to the neural network for accelerated convergence of the learning behavior. An apparatus for performing the color data correction includes an integrated neural network color processor that utilizes a small number of neural elements to reduce the complexity of the color data processing and computational complication.
15 Citations
17 Claims
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1. A method for adaptive color scanning/printing data correction, wherein a color scanning/printing system includes a color image inputting device, a neural network, and a color image outputting device, said inputting device being connected to said neural network, and said neural network being connected to said outputting device, said method comprising the steps of:
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providing pre-selected test color image patterns to said color image outputting device for outputting a first output image; inputting said first output image to said inputting device to obtain color data of said first output image, and processing a learning sample generated with said color data by said neural network; said neural network subsequently taking the average of the data values of all the color picture elements within a neighborhood in the predetermined vicinity of each input color picture element, and taking the average data value of all the color picture elements within the corresponding neighborhood of the corresponding output color picture element, so as to constitute a learning sample pair including the averaged color data values of input and output gamuts respectively; and said neural network processing said generated learning sample pair to perform a neural network learning procedure. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method for adaptive color scanning/printing data correction by neural network back-propagation algorithm, wherein a color scanning/printing system includes a color image inputting device, a neural network, and a color image outputting device, said inputting device being connected to said neural network, and said neural network being connected to said outputting device, said method comprising the steps of:
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(a) providing pre-selected test color image patterns to said color image outputting device for outputting a first output image; (b) inputting said first output image to said inputting device to obtain color data of said first output image, and processing a learning sample generated with said color data by said neural network; (c) said neural network performing a back-propagation balancing algorithm for a learning procedure until the learning error reaches below a predetermined value, wherein said back-propagation algorithm is defined; for output layer k of said neural network,
space="preserve" listing-type="equation">Δ
W.sub.kj =η
δ
.sub.k.O.sub.j
space="preserve" listing-type="equation">δ
.sub.k =(t.sub.k -O.sub.k)(1+O.sub.k)(1-O.sub.k)and for the hidden layer j, ##EQU7## wherein Oi, Oj, and Ok are the outputs of the neural elements in the i, j and k layers of said neural network respectively, tk is the target value of the output layer neural element of said neural network, hp is the hidden layer acceleration parameter, Wkj and Wji are the neural weight values between the k and j layers and between the j and i layers of said neural network respectively, and n is the learning rate parameter. - View Dependent Claims (13, 14, 15)
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16. A method for adaptive color scanning/printing data correction, wherein a color scanning/printing system includes a color image inputting device, a neural network, and a color image outputting device, said inputting device being connected to said neural network, and said neural network being connected to said outputting device, said method comprising the steps of:
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providing pre-selected test color image patterns to said color image outputting device for outputting a first output image; inputting said first output image to said inputting device to obtain color data of said first output image, and processing a learning sample generated with said color data by said neural network; said neural network processing said constituted learning sample, and at the time when the learning error reaches below a first predetermined value, said learning sample being extracted with its grey content to constitute a neutral learning sample for feeding back to said neural network for a re-started learning procedure until the learning error reaches again below a second predetermined value.
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17. A neural network color data correction apparatus for adaptive color scanning/printing, wherein a color scanning/printing system includes a color image inputting device, a neural network, and a color image outputting device, said inputting device being connected to said neural network, and said neural network being connected to said outputting device, said neural network color data correction apparatus comprising:
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means for providing pre-selected test color image patterns to said color image outputting device for outputting a first output image; means for inputting said first output image to said inputting device to obtain color data of said first output image, and processing a learning sample generated with said color data by said neural network means for said neural network to subsequently take the average of the data values of all the color picture elements within a neighborhood in the predetermined vicinity of each input color picture element, and take the average data value of all the color picture elements within the corresponding neighborhood of the corresponding output color picture element, so as to constitute a learning sample pair including the averaged color data values of input and output gamuts respectively; and means for said neural network to process said learning sample pair to perform a neural network learning procedure.
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Specification