Kabushiki Kaisha Toshiba

Bunpei Irie

Tomoyuki Hamamura

Masaya Maeda

Naotake Natori

Yuka Watanabe

Ying Piao

Kenji Baba

Hideo Horiuchi

Yoshiaki Kurosawa

Yasuhiro Ohkawa

Akira Sawada

Toshio Sato

Yasuhiro Aoki

Akihiko Nakao

Takuma Akagi

Shunji Ariyoshi

Haruo Asada

According to one embodiment, a delivery handling apparatus includes a recognition portion which performs an image recognition processing to an image imaged by an imaging portion to image a delivery object, to recognize information including an address given to the delivery object and a parameter selecting portion which sequentially selects parameter sets from a plurality of the parameter sets previously stored in a storage portion and a control portion which makes the parameter selecting portion sequentially select parameter sets from a plurality of the parameter sets, and the recognition portion perform an image recognition processing to an image with the parameter sets selected by the parameter selecting portion, and the parameter selecting portion select the parameter set satisfying a prescribed condition, based on a result of the image recognition processing corresponding to the respective parameter sets.

Delivery handling apparatus, delivery handling method, and delivery handling program

An address recognition apparatus has an address recognition section, and a non-addressee determination section. The address recognition section acquires, based on an image of an object, address information described on the object. The non-addressee determination section determines, based on a comparison result of information relating to first address information that is the address information acquired in the address recognition section at a desired timing, and information relating to second address information that is the address information acquired in the address recognition section before the first address information, whether or not the first address information is a non-destination address that is not an address of an addressee.

Address recognition apparatus, sorting apparatus, integrated address recognition apparatus and address recognition method

A delivery processing apparatus has a recognition unit and a determination unit. The recognition unit executes recognition processing for recognizing information that is provided on a delivery target item based on an image obtained by shooting an image of the delivery target item. The determination unit determines whether or not to extend the recognition processing performed by the recognition unit, based on a degree of progress of the recognition processing that has been performed by the recognition unit in a period from when the information recognition processing was started by the recognition unit until a predetermined time has elapsed, and an extension rate, which indicates a ratio of the number of times that the recognition unit has extended the recognition processing to the number of times that the recognition unit has performed the recognition processing.

Delivery processing apparatus and method for recognizing information provided on delivery target item

A sorting system is provided with conveying section, distance detecting section, article detecting section, determining section, acquisition section, and sorting section. The conveying section conveys an article. The distance detecting section acquires distance data indicating a distance, from above the conveying section, from the distance detecting section to an object included in a detection area including an area through which the article conveyed by the conveying section passes. The article detecting section detects one or a plurality of the articles based on the distance data. The determining section determines, when a plurality of the articles are detected, whether a plurality of the articles are sortable. The acquisition section acquires sorting information of the article.

Sorting system and sorting method

A sorting device has sensors, a plurality of a feature extracting unit, a feature searching unit, a determining unit and a sorting unit. The sensors detect physical quantities of an object. The feature extracting unit extracts values of a plurality of types of feature values from the physical quantities detected. The feature searching unit specifies identification information of the object based on values of various feature values extracted with reference to a feature database which associates and stores the values of the various feature values and the identification information of the object in advance. The determining unit determines sorting information of the object based on the identification information of the object specified with reference to a sorting database which associates and stores the identification information of the object and the sorting information in advance. The sorting unit sorts the object based on the sorting information determined.

Sorting device and sorting method

According to one embodiment, a postal indicium detection method includes detecting whether or not one of a first face and a second face of a sheet corresponds to a picture card specific face, detecting a postal indicium candidate from the second face based on a first detection result indicating that the first face corresponds to the picture card specific face, and detecting the postal indicium candidate from the first face based on a second detection result indicating that the second face corresponds to the picture card specific face.

Postal indicium detection method and postal indicium detection apparatus

According to one embodiment, a barcode processing apparatus comprises a reading unit configured to read an image of a barcode configured by a plurality of bars laid out at a predetermined interval, each bar being formed by a plurality of ink dots, and a barcode recognition unit configured to filter the read image using a mask which has a width smaller than the predetermined interval and larger than a width of one bar, and corresponds to a length of one bar so as to extract a group of a plurality of ink dots, to couple the plurality of ink dots in the extracted group, to detect one bar based on the coupling result, and to recognize a barcode configured by a plurality of detected bars.

Barcode processing apparatus and barcode processing method

An information recognition processing apparatus according to an embodiment of the invention includes a storage unit configured to store statistical information indicating results of identification information recognition processing in which an image of a first object to be read is read to acquire a plurality of first read images of different image brightness levels, and recognition of identification information included in the first read image of each brightness level is tried, an image reading unit configured to read an image of a second object to be read to acquire a plurality of second read images of different image brightness levels, and a recognition unit configured to preferentially execute a recognition process of identification information included in the second read image of a predetermined brightness level of the plurality of second read images of the different image brightness levels, based on the statistical information.

Information recognition processing apparatus and information recognition processing method

An image processing apparatus according to one embodiment of the invention includes a first image reading unit configured to read an image from an object to be read by visible light, a second image reading unit configured to read an image from the object to be read by invisible light, a first detection unit configured to detect a background image from a first read image read by the first image reading unit, a registration unit configured to register feature information indicative of a feature of the background image detected by the first detection unit, and a second detection unit configured to detect an image indicative of code information from a second read image read by the second image reading unit on the basis of the feature information registered in the registration unit.

Bar code processing apparatus

An addressee recognizing apparatus recognizes the addressee of matter to be delivered. A database stores a description format including at least a described position, the number of character lines, and the length of each character line in a sender area on the matter to be delivered. When a scanner obtains an image, a plurality of addressee candidate areas are obtained from the image. The apparatus determines whether the description format for each of the extracted candidates matches the description format for the sender area stored in the database. If the description format for the candidate is determined to match the description format for the sender area, the candidate is prohibited from being recognized as the addressee area.

Addressee recognizing apparatus

An image processing system capable of facilitating the highly accurate character recognition on the colored input images. In this system, an input image data to be processed is entered, and a color separation of the input image data is determined according to geometrical data for each image portion of the input image data, and color data for each image portion and a background of the input image data. Then, the input image data is appropriately processed according to the determined color separation. Also, in this system, at least one of color image data and gray scale image data according to the input image data are stored along with and binary image data according to the input image data, and the binary image data are processed by looking up the at least one of the color image data and the gray scale image data.

Image processing system suitable for colored character recognition

A pattern recognition system capable of handling the non-Gaussian feature vector distribution in the feature vector space such that the recognition rate can be improved while using the pattern matching based on the assumption of the Gaussian feature vector distribution. In the system, a nonlinear transformation for each recognizable category is applied to the feature vector extracted from the input pattern to be recognized, to obtain a transformed feature data for the input pattern, where the nonlinear transformation maps linearly inseparable distributions in a vector space containing the feature vector onto linearly separable distributions. Then, the transformed feature data for the input pattern is compared with reference feature model for each recognizable category indicating a feature vector distribution for each category, to find a category of the input pattern as that of the reference feature model closest to the transformed feature data for the input pattern.

Pattern recognition system with improved recognition rate using

A method and an apparatus for pattern recognition utilizing the multiple similarity method, capable of taking structural features of a pattern to be recognized into account, so that sufficiently accurate pattern recognition can be achieved even when the pattern may involve complicated and diverse variations. The method includes the steps of: counting a number of occurences within each one of localized regions which subdivides a pattern to be recognized, of local patterns indicating possible arrangements of picture elements; deriving a vector quantity indicating distribution of black picture elements which constitute the pattern, from the numbers of occurrences of the local patterns; calculating multiple similarity defined in terms of square of inner product of the vector quantity and one of prescribed standard vectors representing standard patterns; and recognizing the pattern by identifying the pattern with one of the standard pattern whose corresponding standard vectors gives the maximum values for the multiple similarity.

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Kawasaki, Japan

Bunpei Irie