Seiko Epson Corporation

Takashi Hyuga

Toshinori Nagahashi

Kimitake Mizobe

Iwane Ikeda

Kenji Murakami

An image processing apparatus includes a processor. The processor accepts a captured image generated by capturing an image of a target object, detects identification information for identifying the target object by processing the captured image, and generates a combined image that is the combination of the captured image and the identification information and causes a display apparatus to display the combined image. In the combined image, the identification information is superimposed on the target object in the captured image.

Image processing apparatus, robot and robot system

An image processing apparatus includes a processor, in which the processor receives parameter settings including imaging parameters and image processing parameters, executes a processing sequence including imaging and image processing based on the parameter settings to output a result image, determines whether the result image is acceptable or not based on a predetermined determination condition, causes a display unit to display a plurality of reduced images indicating execution results of the processing sequence of the parameter settings as a plurality of result images in a list manner, and displays a determination result on a display area of the plurality of result images.

An ultrasonic measurement apparatus detects a plurality of feature points in a B-mode image acquired by ultrasonic measurement. The feature point detection is repeatedly performed for each measurement frame. Then, a displacement vector of each feature point between measurement frames that are temporally adjacent (consecutive) to each other is calculated. Then, a displacement direction is calculated based on the displacement vector for each feature point. An intersection of the displacement direction lines is detected as a cross-sectional center position of a blood vessel.

Ultrasonic measurement apparatus and ultrasonic measurement method

A printing system that transfers an image composed of pixels of a first resolution, includes a client and a printing apparatus. The client includes a determining unit that, for a pixel block that is of a size of a pixel of a second resolution that is lower than the first resolution, determines whether or not the pixel block is homogenous on the basis of a difference in color information for a target pixel of the first resolution included in the pixel block; an image-data-for-transfer creating unit that creates image data for transfer by changing pixels of the first resolution included in a pixel block that has been determined to be homogenous from the first resolution to the second resolution; and a transmitting unit that transmits the image data for transfer. The printing apparatus includes a receiving unit that receives the image data for transfer and a high-resolution-image-data creating unit that creates image data representing an image composed of pixels of the first resolution by changing pixels of the second resolution in the image data for transfer from the second resolution to the first resolution.

Printing system, printing apparatus and image-printing method for suppressing image quality degradation

A printing system includes: a printing device that prints, using ink, an image including a plurality of pixels each assigned with any one of a plurality of tone values; a server device that distributes printing data of a printing image, and first data that represents a total number of pixels of the printing image on a tone value basis; and a client device that receives the printing data and the first data, and based on the first data and second data that represents an amount of ink per pixel needed for the printing device to print each of the tone values, calculates a required amount of ink needed for the printing device to print the printing image.

Printing system and client device for the same, printing device, printing method, printing program and recording medium for the same

A metadata generating apparatus includes: a private-content-information creating unit that creates content information of an individual; a public-content-information collecting unit that collects public content information for which metadata for retrieval is created; a keyword extracting unit that extracts a keyword, which forms a basis of the metadata for retrieval, from the public content information collected by the public-content-information collecting unit; and a metadata generating unit that generates metadata for retrieval for a private content, which is created by the private-content-information creating unit, on the basis of the keyword extracted by the keyword extracting unit.

Metadata generating apparatus

A head-top detecting method is provided for detecting a head-top of a human face from an image with the human face included therein. After detecting a human face and setting a head-top detecting window at an upper part of the image, an image feature quantity within the head-top detecting window is calculated in a vertical direction and a location in which the image feature quantity changes with a threshold value or more is identified as the head-top of the human face. Thereby the head-top of a human face can be detected accurately and quickly.

Head-top detecting method, head-top detecting system and a head-top detecting program for a human face

An image retrieving system is provided which is suitable for acquiring a retrieving result or a classifying result according to the desire of a user. The system extracts a noticing area from a retrieving key image and each retrieving object image, and a characteristic vector V of these images is generated on the basis of the extracted noticing area. An image similar to the retrieving key image is retrieved from a retrieving object image registration database on the basis of the generated characteristic vector V.

Image retrieving system, image classifying system, image retrieving program, image classifying program, image retrieving method and image classifying method

A method of correcting the deviation of a position at which a human face is detected using a face detection frame F. An image G within the detection frame F is divided left and right along the portion of the center axis C. The degree of similarity of mirror-symmetrical relationship between the image portions G-and G-obtained by the division is calculated. An amount of positional deviation d that maximizes the degree of similarity and its direction are found. The frame F is moved a distance corresponding to the amount of positional deviation d in the direction. Thus, the deviation of the detection position due to the detection frame F can be corrected by a quick and simple method.

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Suwa, Japan

Takashi Hyuga