Hitachi, Ltd.

Xanavi Informatics Corporation

Hiroshi Takenaga

Shoji Muramatsu

Tatsuhiko Monji

Isao Furusawa

Yuji Otsuka

Hiroto Morizane

Jiro Takezaki

Toshimichi Minowa

Hiroshi Kuroda

Satoru Kuragaki

Yuuji Otsuka

Kozo Nakamura

Tokuji Yoshikawa

Tadaaki Kitamura

Kuniyuki Kikuchi

Yasuo Morooka

Mitsuo Kayano

Yoshinori Endo

Kazuaki Takano

Mitsuru Nakamura

Masao Takatoo

Yoshiki Kobayashi

Ken Ohsumi

Nobuhiro Hamada

Ryoichi Komuro

Kazunori Takahashi

Kazuyoshi Asada

Masaaki Fukuhara

Yoshiyuki Okuyama

Hiroyuki Kasuya

Norio Tanaka

Masao Takatou

Masato Suzuki

Shiho Izumi

Yoshio Sakai

Hiromi Inaba

Kiyoshi Nakamura

Toshiro Kinugasa

Yasuhiro Gunji

Korefumi Tashiro

Kenji Yoneda

Junzo Kawakami

Masahiro Kayama

Takeshi Katoh

Masachika Yamazaki

Syoji Kasai

Shigeo Abe

Naofumi Nakata

Kunio Saito

Naoto Oonuma

Masahiro Yasunami

Yukio Asoh

Yukio Asou

Tatsuhiko Monjii

An image pickup device that acquires images is controlled by an image pickup device controller that accepts image acquisition requests from multiple application programs, and an application scheduler selects application programs to be executed. Information indicative of the image data volumes and image data acquisition rates required for each of the multiple application programs is stored and used to select multiple concurrently executable application programs on the basis of the image data volumes and image data acquisition rates. An image acquisition scheduler determines the timing and intervals at which the multiple executable application programs repeat receiving image data from the image pickup device, without overlapping in terms of time. In addition, an operations section, which explicitly presents concurrently executable application programs to a user and commands the startup of these programs, is displayed on a navigation screen menu.

Acquisition scheduler

Image-processing camera with application processing using acquired image data

Image-processing camera system and image-processing camera control method

A traffic environment recognition system includes units for image-processing and information-merging, a radar unit. A network is connected to the image-processing unit. The radar, information-merging, and a vehicle control unit control the traveling operation of the vehicle. The image-processing unit recognizes headway distance, the azimuth, relative speed and width of a preceding vehicle, and the lane position of the host vehicle. The radar unit recognizes headway distance, the azimuth and relative speed of the preceding vehicle. The information-merging unit receives recognition results provided by the image-processing unit. The radar unit through the network, merges and identifies those results. When the recognition results provided by the image-processing unit and the radar unit relate to the same vehicle, output information is produced by the information-merging unit to identify the vehicles as one and the same vehicle and sends the output information through the network to the vehicle control unit.

Traffic environment recognition method and system for carrying out the same

Vehicle image-processing camera system for acquiring images for multiple vehicle applications

An image processing system including an imaging unit mounted on a subject vehicle, and an image analysis unit that acquires images photographed by the imaging unit. The image analysis unit acquires plural images with different exposures that the imaging unit photographed, detects light spots emitted from the other vehicles from the plural images with different exposures, and detects positions of the other vehicles. The plural images are an image photographed with a first exposure, and an image photographed with a second exposure greater than the first exposure. The image analysis unit extracts a first area containing a first color component from the image photographed with the first exposure to determine the first area to be a first three-dimensional object, and extracts a second area containing a second color component from the image photographed with the second exposure to determine the second area to be a second three-dimensional object.

Image processing system and vehicle control system

A photographing system having plural image pickup units for a moving apparatus with enhanced user's visibility of images for a driver of the apparatus. A system control part controls the image pickup units. Image pickup unit picks up images ahead of the moving apparatus. Image pickup unit picks up images aback. System control unit predicts surrounding state of the moving apparatus based on map information or position information and, when the moving apparatus enters a tunnel, issues a control instruction to image pickup unit so as to increase exposure quantity of image pickup device thereof, and then, when level of output image signal of the image pickup unit enters within a specified range, issues a control instruction to image pickup unit so as to increase exposure quantity of the image pickup device thereof.

Photographing system for a moving apparatus

Integrated processing unit captures range images shot by CCD cameras which are respectively provided on front, rear, left and right sides of a vehicle and image processor. Location-allocation unit creates a location-allocation model of an obstacle from the range images and road surface images (heights of images above road surface). Vehicular swept path calculating unit calculates a swept path of each representative point. Collision decision calculates intersection of the obstacle of the location-allocation model with the swept paths of the representative points and judges whether the points cross the obstacle. When a representative point may possibly cross the obstacle, the point is enhanced and displayed together with the obstacle (object) on monitor.

Method and system of monitoring around a vehicle

The invention provides an image processing system capable of precisely locating the positions of the light spots covering near headlights through far tail lamps by using one camera. The invention, discriminating the headlights and tail lamps from noise lights such as a traffic light, streetlight, and vending machine, enhances the vehicle detection performance at night. The system includes an image input means that inputs images in front of a vehicle, an image analysis means that analyzes the images inputted by the image input means. The image input means has a means of photographing more than two images with different exposures. The image analysis means analyzes the images photographed by the image input means to transform them into the position information of the vehicles traveling in front.

A lane marker recognition method comprises the steps of inputting an image including a lane marker, extracting luminance change points in the image, and estimating the position of the lane marker using the extracted edge points. The edge extracting step includes calculating an angle of orientation of each of the edges and the lane marker position estimating step includes extracting edge points that are oriented toward a vanishing point of a road, from among the edge points extracted in the edge extracting step.

Lane marker recognition method

A driving lane recognition system which can improve the lane recognition accuracy by stably detecting the various kinds of lane markers is disclosed. An image processing meansfor image-processing a road image taken by a camerahas a plurality of different kinds of image processing algorithmsto. A driving lane is detected by selecting an image processing algorithm suitable for the driving lane out of the plurality of different kinds of image processing algorithmstocorresponding to a road on which a vehicle is running.

Lane recognition system

An image processing system includes a lamp which emits light to a glass, an imaging device which captures light which is emitted from the lamp and reflected by the glass, and an optical filter, located between the glass and the imaging device, which transmits rays with a specific wavelength of the reflected light. A lens is provided in front of the imaging device, and a focus of the lens is adjusted to a point beyond the glass, and an image processor is provided which processes an image captured by the imaging device and detects moisture on the glass.

Rain/moisture and object imaging system for vehicle

A traffic environment recognition system includes an image-processing unit, an information-merging unit, a radar unit, and a network connected to the image-processing unit, the radar unit, the information-merging unit and a vehicle control unit capable of controlling the traveling operation of a host vehicle. The image-processing unit recognizes headway distance, the azimuth, relative speed and width of the preceding vehicle, and the position of the host vehicle in a lane. The radar unit recognizes headway distance, the azimuth and relative speed of the preceding vehicle. The information-merging unit receives recognition results provided by the image-processing unit and the radar unit through the network, merges the recognition results, identifies recognition objects relating to the recognition results. When a vehicle relating to the recognition results provided by the image-processing unit and a vehicle relating to the recognition results provided by the radar unit are one and the same vehicle, the information-merging unit produces output information by adding a sensor information indicating that the vehicles are one and the same vehicle to the recognition results, and sends the output information through the network to the vehicle control unit.

An image processing system that detects foreign matter on a glass window of a vehicle and objects in front of the vehicle. The system includes an image processor, a first lamp, and a second lamp. On/off control of the first and second lamps is controlled by the image processor. Light from the first lamp is reflected from the outer sauce of the glass when raindrops are present on the outside of the glass. Light from the second lamp is reflected from the inner surface of the glass when moisture is present on the inside of the glass. Any reflected light goes through a lens and an optical filter with prescribed optical characteristics to an image device. The lens is focused to a point beyond the window so that the image processor an also detect objects in front of the vehicle.

Image processing system which processes an image captured by an imaging device through a lens having a focus which is adjusted to a point beyond the glass

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Naka, Japan

Hiroshi Takenaga