Nidec Sankyo Corporation

Sankyo Seiki Mfg. Co., Ltd

Kabushiki Kaisha Sankyo Seiki Seisakusho

Seiko Epson Corporation

Hiroshi Nakamura

Mitsuo Yokozawa

Keiji Hoson

Shinya Morozumi

Shogo Momose

Fusayoshi Aruga

Junichi Nakajyo

Keiichi Enomoto

Masahiro Hatanaka

Hayato Kobayashi

An injection molding machine management system includes an injection molding machine, a first detecting section configured to detect at least one of a physical quantity of the injection molding machine and a physical quantity of a molded article, an on-premise server, and a Cloud server. The Cloud server includes a first storing section configured to store information concerning at least one of the physical quantity of the injection molding machine and the physical quantity of the molded article detected by the first detecting section and a virtual machine configured to generate a control rule for the injection molding machine based on the information. The on-premise server includes a second storing section configured to store the control rule and a control section configured to perform, based on the control rule, control of the injection molding machine corresponding to at least one of the physical quantity of the injection molding machine and the physical quantity of the molded article detected by the first detecting section.

Injection molding machine management system

A symbol information reader may include an imager; an image memory configured to save image data of a recording medium; and a position detecting processor configured to retrieve the image data and detect the positions of symbols on the recording medium. The position detecting processor may be configured to calculate the amount of change in luminance value of scanning lines in a predetermined area of the image data and discriminate a provisional area possibly corresponding to the symbol, acquire correlations of the provisional area with neighboring areas and create a map showing an area with high correlation values, search the correlation map for the presence of the symbols and label on areas judged having the symbols, set an area for each of the multiple symbols and makes divisions, and detect positions of the symbols printed on the recording medium.

Symbol information reader and symbol information reading method

A character recognition device may include an image sensor to acquire image and a data processor configured to segment a character string from the image data. The data processor may be configured to detect positions to segment the characters; set an area to detect a position for segmenting characters; create a first projection of pixel values arranged in the character arrangement direction along which characters are arranged and a second projection of pixel values arranged in an orthogonal to said character arrangement direction; calculate a synthetic threshold value of a first threshold, acquired by applying a discriminant analysis method on said first, X-axis projection, and a second threshold, acquired by applying said discriminant analysis method on said second, Y-axis projection, and take it as a binary threshold for said setting area; and acquire character segmenting positions based on said binary threshold.

Character segmentation device, character recognition device and character segmentation method

A character segmenting apparatus may include a character segmenting position detecting unit to detect a segmenting position of characters. The character segmenting position detecting unit may include an area setting unit to set up an area for detecting the segmenting position; a projection creating unit configured to create a projection of pixel values, with respect to pixels arranged in a character placement direction, at least in a specified area set up by the area setting unit; a binarizing threshold value obtaining unit to calculate a moving average on the basis of minimum pixel values of the projection, in order to specify the moving average as a binarizing threshold value for the specified area; and a position detecting unit to calculate a character segmenting position on the basis of the binarizing threshold value.

Character segmenting apparatus, character recognition apparatus, and character segmenting method

A stack barcode reader may include an imager configured to image the stack barcode; an image memory configured to store an image datum of the stack barcode; and a data processor including a decoder configured to decode an encoded information expressed as the stack barcode, on the basis of the image datum. The decoder may be configured to measure width of a bar and a space of the stack barcode; measure a T-sequence, being a sequence of numerical values, according to line width of a bar and a space of the stack barcode; obtain a code-word corresponding to the T-sequence; and compare a cluster value obtained from the T-sequence with a theoretical cluster value, and modify the T-sequence by using the theoretical cluster value and the conversion table of T-sequence/code-word if there appears a difference between the two cluster values.

Stack barcode reader and stack barcode reading method

A character recognition device for use with a medium with a character string, the character recognition device may include an image reader to capture the character string as image data; an image memory to store the image which is read by said image reader; and a data processor to segment the character string from said image data stored in said image memory and segmenting characters from said character string for character recognition. The data processor may include a character segmenting unit to detect boundary positions of neighboring characters in said character string and segment each character. The character segmenting unit may include a boundary search range setting unit to set a range to search boundary position of neighboring characters in said character string and a boundary position setting unit to set a boundary position of characters by using a discriminant analysis method within said search range which has been set.

Character recognition device and character segmentation method

A character recognition apparatus may include an imaging element configured to read a character string placed on an information recording medium; an image memory configured to store image data of the character string; and a character segmenting unit configured to segment a character constituting the character string. The character segmenting unit may include a minimum intensity curve creating unit configured to detect a minimum intensity value among light intensity values, and create a minimum intensity curve of the image data according to the minimum intensity value of each pixel row; a character segmenting position detecting unit configured to calculate a space between the characters neighboring in the created minimum intensity curve, in order to detect a character segmenting position between the characters; and a character segmenting process unit configured to segment each character according to the detected character segmenting position between the characters.

Apparatus, method, and program for character recognition using minimum intensity curve of image data

A character segmentation section, for segmenting characters of a character line may include a minimum pixel-value curve creating section configured to extract a smallest pixel value in pixels composing a pixel line arranged in a direction orthogonal to a character line direction in said multi-level image data and create a minimum pixel-value curve, a character partitioning position determining section configured to determine partitioning positions of said characters, based on said minimum pixel value curve, a binarization processing section configured to detect a minimum pixel value indicating said linear drawing from said minimum pixel-value curve, acquires a binarization threshold based on said minimum pixel value, and binarizes said multi-level image data using said binarization threshold, and a character segmentation implementing section configured to extract the image data of each character.

Character segmentation device and character segmentation method

An image processing device may include an image scanning unit; an image memory; a sample area designating unit; a binarization unit for implementing a filtering process on a scanned multi-valued image, to produce the compensated image data and for binarizing the compensated image data; a correlation operation unit for acquiring each of the correlations between the binary image data and the scanned multi-valued image data; and an optimal binarization information selecting unit for selecting the optimal parameter value or binary image data based on the correlations. The binarization unit may include a parameter value setting section, a filtering process section, and a binarization process section for binarizing each of the compensated image data based on a predetermined binary threshold.

Image processing device, an image processing method and a program to be used to implement the image processing

A stack barcode reader may include an imaging section configured to image the stack barcode in which character information is expressed with a bar and a space; an image memory configured to store image data of the stack barcode; a data processing section including a decoding unit and configured to decode the barcode of the stack barcode into the character information. The decoding unit may include a low-level decoding unit, a high-level decoding unit, and a decoded result selection unit for selecting a decoded result. The high-level decoding unit may include an error-correction unit. The decoded result selection unit may include a counter unit configured to count the number of error corrections and a selection unit configured to select a decoded result having the less number of corrections.

An image combining device may include an image reading unit that reads an image of a first and second partial area which have a portion overlapping; a template area setting section that sets apart an area of a predetermined shape as a comparison area from the overlapping area; a calculation area setting section that selects areas of the shape corresponding to the shape of the comparison area; a correlation coefficient calculating section that calculates a correlation coefficient between each of the image data values of the multiple areas; an area identifying section that identifies, from the multiple areas, the area in which the calculation result satisfies a predetermined condition; and a combining section that combines the images of the first and second partial areas in the positional relationship in which the area identified by the area identifying section and the comparison area overlap with each other.

Image combining device, image combining method and program to implement image combining method

An apparatus and method for reading symbol information enabling improvement of decoding accuracy, not being affected by the condition of a reflection coefficient waveform of a reflected light beam and the kind of symbol information to be read. The method includes: reading a reflected light beam from symbol information irradiated with a light beam; detecting peak values in a reflection coefficient waveform of the reflected light beam; calculating a first peak value according to a peak value at a high reflection coefficient side (white level) among the peak values detected; calculating a second peak value according to a peak value at a low reflection coefficient side (black level) among the peak values detected; and calculating a binarization threshold based on the first peak value and the second peak value.

Apparatus and method for reading symbol information

A method and an apparatus for character string recognition may be provided that enables prevention of a decrease in recognition accuracy for a character string even when distortion of an image appears in a direction perpendicular to a medium transfer direction.

Method and apparatus for character string recognition

Provided is a method and an apparatus for reading barcode information; the method and apparatus being able to read barcode information correctly without being influenced by the environmental conditions at the time of reading the barcode information. When a reading method according to a prescribed rule could not read a character, each element width is judged again to be either thin or thick according to structural characteristics of characters to convert again an element width matrix into a bit pattern, and then a character corresponding to the bit pattern as a result of the re-conversion is determined.

Method and apparatus for reading barcode information

A character line recognition method for processing image data obtained by scanning a character line on a medium to recognize the character line may include processing the image data into monochrome binary format image data by using a predetermined binarization standard threshold; extracting character features from each character that composes the character line to calculate similarity with respect to standard character features; temporarily determining characters based on the similarity; calculating basic statistics of the similarity for all the characters which have been temporarily determined; and changing the binarization standard threshold based on the basic statistics and then returning to the processing the image data.

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Nagano, Japan

Hiroshi Nakamura