Abstract: A head-up display device includes an image display device that outputs display light of an image; a mirror having a reflecting surface that reflects the display light toward a reflecting portion, and an input shaft; a motor that has an output shaft located on an extended line of the input shaft, and rotates the output shaft; a transmission member that has a cylindrical fitting portion to which the input shaft is press-fitted and a coupling portion coupled with the output shaft and transmitting output torque of the motor from the output shaft to the input shaft; a holding member that holds the motor; and a first spring that is interposed between the holding member and the transmission member, and imparts, to the transmission member, a biasing force oriented to bring the mirror close to the output shaft.

Abstract: A head-up display device includes an image display device that outputs display light of an image; a mirror having a reflecting surface that reflects the display light toward a reflecting portion, and an input shaft; a motor that has an output shaft located on an extended line of the input shaft, and rotates the output shaft; a transmission member that has a cylindrical fitting portion to which the input shaft is press-fitted and a coupling portion coupled with the output shaft and transmitting output torque of the motor from the output shaft to the input shaft; a holding member that holds the motor; and a first spring that is interposed between the holding member and the transmission member, and imparts, to the transmission member, a biasing force oriented to bring the mirror close to the output shaft.

Abstract: An image processing apparatus includes a calculating unit and a detecting unit. The calculating unit calculates an additional value of a luminance values for each coordinate value in a first direction. The calculating unit calculates an additional value of the luminance values for each coordinate value in a second direction. The detecting unit detects a region of the image in which additional values of the luminance values for each coordinate value in the first direction are equal or a region in which additional values of the luminance values for each coordinate value in the second direction are equal.

Abstract: An image processing apparatus 10 according to an embodiment includes a detection unit 11 and an identification unit 12. The detection unit 11 included in the image processing apparatus 10 detects a region in which a pixel value is changed between frames included in moving image data. The detection unit 11 outputs a detected result to the identification unit 12. The identification unit 12 sets a circumscribed rectangle to the region detected by the detection unit 11. The identification unit 12 specifies a frame including a detection target based on a filling ratio of the region to the circumscribed rectangle.

Abstract: An image processing apparatus includes a processor. The processor is configured to execute a process including creating an average image of difference images in moving picture data based on a difference between a first frame and a second frame adjacent to the first frame, the first frame and the second frame included in the moving picture data, calculating a sum total of luminance values arranged in a lateral direction of the average image for each point in a longitudinal direction of the average image, selecting a predetermined number of points that are higher in value of a secondary differential value of the sum total of luminance values, from among points located in a downward direction from a position of a vanishing point in the average image, and firstly specifying a point that is on a boundary between a hood and a road from among the predetermined number of selected points.

Abstract: An image processing apparatus includes a calculating unit and a detecting unit. The calculating unit calculates an additional value of a luminance values for each coordinate value in a first direction. The calculating unit calculates an additional value of the luminance values for each coordinate value in a second direction. The detecting unit detects a region of the image in which additional values of the luminance values for each coordinate value in the first direction are equal or a region in which additional values of the luminance values for each coordinate value in the second direction are equal.

Abstract: An image processing apparatus according to an embodiment has an identification unit, a detection unit, and a determination unit. The image processing apparatus according to the embodiment identifies moving image data taken by a camera in the night-time and detects a high-brightness region from frames of the identified moving image data. The image processing apparatus determines whether or not the high-brightness region is a subject to be detected, in a switchable manner depending on whether the moving image data has been taken during curve running or straight running.

Abstract: An image processing apparatus 10 according to an embodiment includes a detection unit 11 and an identification unit 12. The detection unit 11 included in the image processing apparatus 10 detects a region in which a pixel value is changed between frames included in moving image data. The detection unit 11 outputs a detected result to the identification unit 12. The identification unit 12 sets a circumscribed rectangle to the region detected by the detection unit 11. The identification unit 12 specifies a frame including a detection target based on a filling ratio of the region to the circumscribed rectangle.

Abstract: An image processing apparatus includes a processor. The processor is configured to execute a process including creating an average image of difference images in moving picture data based on a difference between a first frame and a second frame adjacent to the first frame, the first frame and the second frame included in the moving picture data, calculating a sum total of luminance values arranged in a lateral direction of the average image for each point in a longitudinal direction of the average image, selecting a predetermined number of points that are higher in value of a secondary differential value of the sum total of luminance values, from among points located in a downward direction from a position of a vanishing point in the average image, and firstly specifying a point that is on a boundary between a hood and a road from among the predetermined number of selected points.

Abstract: The pixels located at equal intervals in a shot image are converted into intensity components and applied with a differential filter. The number of the obtained variations that have values larger than or equal to a certain value among the obtained variations is counted. Then discrimination of a vehicle shot in the target image is executed on the basis of the counted value. The counted value varies depending on a size of a shot object in a shot image. The counted value is large when an occupied area of the object is large, and the counted value is small when the occupied area of the object is small. By so doing, it is advantageously possible to properly discriminate a vehicle.

Abstract: A recognition device includes a component identifying unit, an identification-region defining unit, a vehicle-image generating unit, and a data reduction-level setting unit. The component identifying unit identifies a component of a vehicle in an original image. The identification-region defining unit defines an identification region including an identification component for identifying the vehicle based on the component. The vehicle-image generating unit extracts the identification region and generates a vehicle image. The data reduction-level setting unit sets a data reduction level based on which a vehicle image is to be generated from an original image satisfying a predetermined condition.

Abstract: A vehicle-type determination apparatus includes a vehicle-portion extracting unit, a hood recognizing unit, and a vehicle-type determining unit. The vehicle-portion extracting unit extracts a vehicle portion from an image of a recognition object. The hood recognizing unit recognizes an area corresponding to a hood in the vehicle portion extracted by the vehicle-portion extracting unit. The vehicle-type determining unit determines the vehicle type based on the degree of inclination of a side of the hood area recognized by the hood recognizing unit.

Abstract: A color classification method including: determining a plurality of predetermined process target regions from a plurality of pickup images taken by an imaging device; calculating a plurality of color distributions of pixels contained in the respective determined process target regions; and forming a plurality of clusters by executing a clustering process based on the calculated color distributions for the pickup images, the method being for classifying a plurality of colors with respect to the respective formed clusters, the forming step including: extracting predetermined number of the classified colors, whose calculated rates are highest in the calculated plurality of the rates, from among the predetermined classified colors; defining a plurality of color spaces, dimensions of each of which are selected from the predetermined number of the extracted classified colors.

Abstract: This invention is a technique to presume colors of an image. A color extraction method according to this invention include a luminance calculation step of calculating a luminance in a color extraction region, which is included in an image and from which a color is to be extracted, and storing the calculated luminance into a storage device; a color name extraction of referring to a luminance database storing a color name and a luminance corresponding to the color name to extract a color name in the color extraction region by using, as a main judgment element, the luminance in the color extraction region, which is stored in the storage device. As a result, it is possible to presume a color even in a case of the monochromatic image or color image photographed in the night.

Abstract: A bandwidth control server, a bandwidth control program recorded on a computer readable record medium, and a monitoring system that control the sending of image data obtained by cameras in accordance with priority corresponding to a situation. A setting information storage section stores setting information regarding a camera installed at each point. When disaster information is acquired, a disaster detection section extracts a disaster type and a disaster area from the disaster information. A priority determination section searches the setting information on the basis of the disaster type and the disaster area and extracts setting information corresponding to the disaster type. Then the priority determination section determines priority for sending image data obtained by cameras installed in the disaster area on the basis of the extracted setting information.

Abstract: A vehicle search system is provided, which is capable of easily and efficiently searching for a particular vehicle image based on vague and uncertain information. The vehicle search system includes an image database for accumulating vehicle images photographed by a stationary camera placed on the road under a condition that the vehicle images are associated with at least photographing date and time information and photographing place information of the vehicle image; an image recognizing part for extracting feature information (vehicle color, vehicle shape, etc.

Abstract: A method, device and computer program for mobile object information management program includes obtaining a first image by photographing identification information of a mobile object, executing character recognition process on the first image to obtain a first character recognition result, determining accuracy of the first character recognition result, registering, as the identification information corresponding to the mobile object, a plurality of first character recognition results, for each of which the accuracy is determined as low, and outputting the first character recognition results registered.

Abstract: An apparatus for setting an image-capturing condition includes a travel direction storing unit that receives information on a travel direction of a moving object, and stores the information received, and an image-capturing condition setting unit that sets, based on the information stored, a condition for capturing an image that includes identification data for identifying the moving object.

Abstract: A bandwidth control server, a bandwidth control program recorded on a computer readable record medium, and a monitoring system that control the sending of image data obtained by cameras in accordance with priority corresponding to a situation. A setting information storage section stores setting information regarding a camera installed at each point. When disaster information is acquired, a disaster detection section extracts a disaster type and a disaster area from the disaster information. A priority determination section searches the setting information on the basis of the disaster type and the disaster area and extracts setting information corresponding to the disaster type. Then the priority determination section determines priority for sending image data obtained by cameras installed in the disaster area on the basis of the extracted setting information.

Abstract: A color classification method including: determining a plurality of predetermined process target regions from a plurality of pickup images taken by an imaging device; calculating a plurality of color distributions of pixels contained in the respective determined process target regions; and forming a plurality of clusters by executing a clustering process based on the calculated color distributions for the pickup images, the method being for classifying a plurality of colors with respect to the respective formed clusters, the forming step including: extracting predetermined number of the classified colors, whose calculated rates are highest in the calculated plurality of the rates, from among the predetermined classified colors; defining a plurality of color spaces, dimensions of each of which are selected from the predetermined number of the extracted classified colors.