Matsushita Electric Industrial Co., Ltd.

Matsushita Research Institute Tokyo, Inc.

Matsushita Graphic Communication Systems, Inc.

Kunio Yoshida

Motohiko Naka

Hiroaki Kotera

Yukifumi Tsuda

Mie Saitoh

Takehiko Shida

Hiroyoshi Tsuchiya

Takehisa Tanaka

Heijiro Hayami

Yoshimitsu Kanno

Masaaki Sato

Makoto Shimizu

Ikuo Akamine

Tsutomu Shibata

Toshiki Kindo

Katsuhiko Fujiwara

Akira Yokouchi

Ryuzo Kan

Akira Taomoto

Shiro Asakawa

Akiyoshi Tanaka

Toyoki Kawahara

Atsuharu Yamamoto

Kunio Sannomiya

Mikio Fujita

Shigeo Komizo

Takayuki Imai

Yoshihiro Uno

Katsuhiro Nichogi

Hiroaki Miwa

Toru Asano

Haruko Sugita

Yoshiaki Uchida

Ryuzo Itabashi

An image input section enters a document image including a bar code, and converts the document image into a binary image. A small pattern removing section removes small patterns from a binary image sent from the input section. A labeling section separates the binary image into labeled regions and calculates the feature quantity including a center position of each labeled region. A region detecting section makes a group of labeled regions spaced at a predetermined positional relationship based on their feature quantities and detects a bar code candidate region. A decoding section decodes the bar code based on the feature quantity involved in the bar code candidate region.

Bar code image processing apparatus

A picture processing apparatus is composed of an infrared ray sensor for producing an infrared picture in which a heat distribution of a measured area is recorded, a picture processing section for processing the infrared picture to extract pieces of personal characteristic data and environmental characteristic data from the infrared picture, and a picture information detecting section composed of a neural network for detecting pieces of personal information and environmental information according to the characteristic data. To be concrete, one or more human-areas respectively recording one or more persons are picked out from the infrared picture, and representative points of the human-areas, the number of human-areas, the number of pixels in each of the human-areas and shapes of the human-areas are extracted as the personal characteristic data. Also, the number of persons in each of the human-areas, foot positions of the persons, person's postures, skin temperatures of the persons and the volume of person's clothes are detected as the personal information according to the personal and environmental characteristic data.

Picture processing apparatus for processing infrared pictures obtained

A pattern classification system includes a plurality of classification sections. Each of the classification sections includes a device for storing information of N coefficients W representing a reference pattern, a device for calculating an evaluation value V on the basis of N input signals S and the N coefficients W, the N input signals representing an input pattern, the evaluation value V representing a relation between the input pattern and the reference pattern, a device for storing information of a fixed threshold value R, and a device for comparing the evaluation value V and the threshold value R and for outputting an estimation signal depending on a result of the comparing, the estimation signal including a category signal P which represents a category. A selection section is operative for selecting one of categories in response to the category signals outputted from the classification sections and for outputting a signal Px representing the selected one of the categories. An adjustment section is operative for adjusting parameters in the classification sections in response to the output signal Px of the selection section and a teacher signal T, the parameters including the coefficients W.

Pattern classification system

An artificial neural function circuit includes an organic thin film element having a resistance state which changes in dependence on an electrical signal inputted thereto and exhibits information processing function similar to that of a nervous system. The organic thin film element has such physical properties that the changed resistance state is held as it is at least for a predetermined time period even after removal of the electric input signal and that the direction in which the resistance is increased or decreased depends on the polarity of the electric input signal. As an example of such organic thin film, a lead phthalocyanine thin film is employed.

Artificial neural function circuit having organic thin film elements

An automatic adjusting apparatus for adjusting equipment which comprises an adjustment state detecting section and a processing section. The detecting section detects an adjustment state of the equipment so as to output one or a plurality of adjustment state indexes on the basis of the detected adjustment state and the processing section performs the process on the basis of the adjustment state index to adjust the equipment. The processing section is equipped with an adjustment state evaluation section for calculating and outputting, on the basis of the adjustment state index, an adjustment evaluation value and an adjustment amount calculation section for calculating, on the basis of the adjustment state index, adjustment amounts for one or a plurality of portions of the equipment. Also included in the processing section is an adjustment control section for selecting, on the basis of the adjustment evaluation value, an adjustment amount from the outputs of the calculation section. The control section controls the calculation section so as to control the adjustment amount on the basis of the selection result. The calculation section has a function to learn the relation between the adjustment state index and the adjustment amount and a function to calculate the adjustment amount in accordance with the learned relation.

Automatic adjusting apparatus for equipment

A coloring device includes an image sampling device for sampling an input signal block representing a group of n.times.m pixels of a monochromatic image and for outputting first signals representing the sampled pixels of the input signal block of the monochromatic image; and artificial neural network, a connection for providing to the artificial neural network, substantially simultaneously, pattern information on patterns to be contained in the monochromatic image and color information on first data indicating colors given to the patterns indicated by the pattern information prior to generation of a color image signal, the artificial neural network having internal state parameters which are adaptively optimized by using a learning algorithm prior to the generation of a color image, the artificial neural network operating for receiving data representing the first signal, for determining which of colors preliminarily and respectively assigned to patterns to be contained in the group of pixels of the monochromatic image represented by the input signal block is given to a pattern actually contained in the group of pixels represented by the input signal block and for outputting second signals representing second data on three primary colors which are used to represent the determined colors given to the patterns actually contained in the group of pixels represented by the input signal block; and a color image storing device for receiving the second signals outputted from the artificial neural network, for storing the received second signals in locations thereof corresponding to the positions of the pixels represented by the input signal block and for outputting third signals representing the three primary color component images of the pixels represented by the input signal block; wherein the image sampling device further functions for scanning the whole of the monochromatic image by generating successive input signal blocks representing successive groups n.times.m pixels to be sampled, thereby outputting third signals for all pixels of the monochromatic image.

Coloring device for performing adaptive coloring of a monochromatic image

A color correction apparatus for use in an apparatus such as a color copier for operating on data obtained by scanning and color analysis of a source image to obtain color density data for use in printing a copy of the source image, the correction apparatus containing a neural network. Parameter values of the neural network are established by repetitive computations based on amounts of difference between color density data previously used to print a plurality of color samples and color density data produced by the neural network in response to color analysis data obtained by analyzing these color samples.

Color data correction apparatus ultilizing neural network

An apparatus for printing signal correction and printer operation control, for use in applications such as color copiers, utilizes a neural network to convert input image signals, derived for example by scanning and analyzing an original image, into printing density signals which are supplied to a printer. In addition, a detection signal expressing at least one internal environmental condition of the printer, such as temperature, is inputted to the neural network, so that the output printing density signals are automatically compensated for changes in internal environment of the printer.

Printing signal correction and printer operation control apparatus

A data compression and recovery apparatus compresses picture element data of a color image by expressing two primary color values of each picture element as a set of parameter values of a neural network in conjunction with reference color data values of a corresponding block of picture elements. Date recovery is achieved by inputting each block of reference color values to a neural network while establishing the corresponding set of parameter values in the network, to thereby obtain the original pair of encoded primary color values for each of successive picture elements. The third primary color can be used as the reference color.

Color image data compression and recovery apparatus based on neural

In a band compression method using an adaptive prediction system preferably applicable to facsimile transmission, a method of selecting picture elements to be referred (hereinafter defined as reference picture elements) for predicting an information value of a picture element wherein the reference picture elements are not selected uniformly and continuously from the neighborhood of the predicted picture element, but a group of picture elements (the first order picture elements) adjacent to the predicted picture element and further a group of picture elements of equal or higher order than the third order are selected as reference picture elements by excluding those shaded picture elements which lie on lines connecting the predicted picture element and the first order picture elements.

Method of band compression

A color image duplicating device comprises a function generator (60) for generating a plurality of functions of n degree wherein elements of color separated data (201, 202, 203) from a color original (1) are variable, a storing device (66) for storing predetermined coefficients, and an arithmetic unit (61, 62, 63) for performing the calculation to find the product and sum of outputs from the function generator (60) and that of the storing device (66). An output from the arithmetic unit (61, 62, 63) is applied to a color recorder (3) to form a color duplicated image.

Color image duplicating system

To overcome the tendency of the recording head of a dot printer to become inoperative in a range below a threshold level, a gray scale input signal is modulated with an oscillating signal so that the modulated signal oscillates above and below the threshold level to reproduce halftone values below the otherwise inoperative range.

Dot printer for reproduction of halftone images

Light beams scans patterns of a subject copy, being reflected therefrom, and being converted into pulsating electrical signals. Color borders between two different colored patterns are detected based on the pulsating signals. On the other hand, a color of a predetermined scanned line following each of the color borders is sensed for determining the sensed color as a color between the adjacent color borders.

Method of and a system for color separation

A color print painted with different colors C.sub.i (i = 1, 2 . . . n) is scanned by a color scanner along a plurality of successive line paths to generate a set of electrical signals each representing the intensity of the spectral components of the light reflected from an elemental area of the print. A macroscopic color separator is provided to generate a set of electrical signals each representing the average spectral intensities per unit area of the print. A data processor is used to compute the probability P(C.sub.i) from the data obtained from the macroscopic color separator and a set of mean spectral intensities exhibited by the color samples with which the print is painted by artisans. In accordance with the Bayes' Rule, the processor then executes computation of the product of P(C.sub.i) and the conditional probability of occurrence of elemental color spectral intensities given that the elemental area being scanned belongs to a particular color sample, using the data received from the color scanner as it scans the print.

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Kawasaki, Japan

Kunio Yoshida