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This paper presents a new approach for the design of feature-extracting recognition networks that do not require expert knowledge in the application domain. Feature-Extracting Recognition Networks (FERNs) are composed of interconnected functional nodes (feurons), which serve as feature extractors, and are followed by a subnetwork of traditional neural nodes (neurons) that act as classifiers. A concurrent evolutionary process (CEP) is used to search the space of feature extractors and neural networks in order to obtain an optimal recognition network that simultaneously performs feature extraction and recognition. By constraining the hill-climbing search functionality of the CEP on specific parts of the solution space, i.e., individually limiting the evolution of feature extractors and neural networks, it was demonstrated that concurrent evolution is a necessary component of the system. Application of this approach to a handwritten digit recognition task illustrates that the proposed methodology is capable of producing recognition networks that perform in-line with other methods without the need for expert knowledge in image processing.

Linear Pixel Shuffling (LPS) dithering produces blue-noise-like patterns, but the placement of thresholds in a dither matrix is a result of an exact algebra, rather than iterative procedure -- as is usually the case. In this paper, we investigate the potential use of LPS for construction of color (CMYK) dithering masks. In case of LPS dithering, the addition of the same value to each mask threshold, using modular arithmetic, is equivalent to the spatial mask shift. We propose a set of three shifted color masks for C, M, and Y that we construct from the original LPS mask using modular arithmetic. The main advantage of this approach is its simplicity. These shifts can be "tailored" to the statistical properties of the image and the set of new screens can be calculated on the fly. The proposed method enables creation of screens of arbitrary size, since the dithering masks are tiled automatically (actually, the masks are of unlimited size). The number of gray levels in each screen is limited by the choice of a modulus number used for mask thresholds calculation. This enables us to use a virtually unlimited number of thresholds that are not necessarily linearly related to the LPS calculated matrix values. Thus, it is relatively easy to construct a non-linear dither screen that will compensate for any printer non-linearity.

A model to predict colorimetric value for color printers is presented. The Neugebauer narrow-band color mixing model wasapplied with modifications. While sixteen primaries are used for four-color printing process in Neugebauer model, we usedtwo data sets in our model, one with eighty-one CMYK primaries and the other with one hundred twenty-five CMY primaries.Two Yule-Nielsen factors were applied to optimize the CMYK set and the CMY set separately. The Yule-Nielsen factorswere optimized by minimizing LE*L*a*b* or LE*94. The Neugebauer colorimetric quality factor (CQF) was applied as aweighting function to optimize dot areas. By optimizing primaries and applying the CQF weighting function, the averagecolor error and the maximum color error decrease significantly.Keywords: color calibration, colorimetric, halftone, color printing, color difference 1. INTRODUCTION In 1936, Murray and Davies' published a model to predict the tone reproduction of binary printing process. This model wasextended by Neugebauer2 in 1937 for color halftoning. However, variation from this linear optical model is often significant.Yule and Nielsen3 modified the tone reproduction model in which they incorporated an empirical factor n to fit the non-linearrelationship between total reflectance and dot area. Viggiano4' further improved the model by applying the Yule-Nielsenfactor n into the Neugebauer narrow-band model. This model and its variations have been widely used to model binary colorprinters'5. Another model, Kubelka-Munk equation was also used for printer color formation by many authors'20. Arney'smodel2' preserves the linearity of the Murray-Davies equation, and explains the reflectances of paper and inks as functions ofdot areas. Balasubramanian22 extended the Neugebauer model into a cellular framework model in which the primary colorsare not limited to sixteen. Due to the increase number of primaries in the cellular model, it yields more accurate result from afiner interpolation. Zeng23 applied the Neugebauer colorimetric quality factor (CQF)24' 25 to optimize the dot areas ofcolorants for the narrow-band Neugebauer model and for the cellular model. By using this model, the color error decreasessignificantly.In this paper, a model modified from Nuegebauer model is presented in which variable primaries can be used. By optimizingthe number and the locations of the primaries, optimizing the Yule-Nielsen n factors, and applying Neugebauer CQFweighting, very small color error can be achieved.