Abstract: A turbidity degree calculating unit calculates a degree of the white turbidity U on a surface of the lens based on a brightness gradient g of an image I (x, y), and a lens cleaning control unit sets a lens cleaning mode for spraying at least one of the cleaning fluid and the compressed air, which is performed by the lens cleaning unit, based on the calculated turbidity degree U.

Abstract: An in-vehicle image recognizer effectively detects a moving object from an image even when a lens has grime. In a detection sensitivity adjustor (50) which adjusts detection sensitivity to be increased according to a white turbidity level (U), the detection sensitivity of a vehicle detector (70) (image recognition application execution unit), which detects the other vehicle (6) (moving object) existing in the surrounding area of a vehicle (5) with a predetermined detection sensitivity from the image obtained by an imaging unit (10) disposed in the vehicle (5) to observe the surrounding area of the vehicle (5) through a lens (12) and convert the light signal of the observed surrounding area of the vehicle (5) into an image signal, is corrected based on the attachment level M of the attached matter such as dirt or water drops to the lens (12), which is calculated by an attachment level calculator (26).

Abstract: A three-dimensional object detection device has an image capturing unit, an object detection unit, first and second edge intensity calculation units, a day/night assessment unit and a controller. The day/night assessment unit assess whether it is currently daytime or nighttime when detecting a three-dimensional object based on the captured images. Upon assesses it is daytime, edges of a subject are extracted from a first edge extraction area, including a horizon reference area, and a threshold value for detecting the three-dimensional object is set based on the intensity of the edges in the first edge extraction area. Upon assesses it is nighttime, the edges of a subject are extracted from a second edge extraction area, including a road edge reference area, and a threshold value for detecting the three-dimensional object is set based on the intensity of the edges that are extracted from the second edge extraction area.

Abstract: A three-dimensional object detection device is provided with an image capturing device, a three-dimensional object detection unit, a rainfall state detection unit, a three-dimensional object assessment unit and a controller. The image capturing device captures an area rearward of a vehicle. The three-dimensional object detection unit detects a three-dimensional object rearward of the vehicle and calculating a traveling speed of the three-dimensional object, based on images obtained by the image capturing device. The rainfall state detection unit detects a state of rainfall including cases of rainfall or formation of a water film on a road surface due to rainfall. The three-dimensional object assessment unit accesses the three-dimensional object to be another vehicle when the traveling speed of the detected three-dimensional object lies within a preset setting range. The controller changes the traveling speed setting range to be narrower when the rainfall state detection unit has detected a rainfall state.

Abstract: A three-dimensional object detection device has an image capturing unit, a three-dimensional object detection unit, a host vehicle speed detection unit, a light source detection unit and a controller. The image capturing unit captures images rearward of a vehicle. The three-dimensional object detection unit detects a presence of a three-dimensional object in a detection area, based on the captured images. The host vehicle speed detection unit detects a vehicle traveling speed. The light source detection unit detects a headlight light source of a headlight of another vehicle. The controller compares the traveling speeds of the object and the vehicle upon not detecting the headlight light source, and suppresses detection of the object upon determining one of the object traveling speed being equal to or less than the vehicle traveling speed, and a difference between the object and vehicle traveling speeds being less than a predetermined value.

Abstract: A camera device includes image capturing device, a lens cleaning device, an adhesion state assessment unit and a controller. The image capturing device is installed on a vehicle and has a lens for forming an image of the vehicle surroundings. The lens cleaning device cleans the lens by spraying a cleaning fluid on the lens in accordance with a predetermined lens cleaning step, in which at least a supply time for supplying cleaning fluid to the lens surface is predetermined. The adhesion state assessment unit is programmed to assess an adhesion state of contamination from a distribution of pixels corresponding to foreign matter adhered to the lens based on a captured image. The controller is programmed to extend the time until a time to start supplying the cleaning fluid in the lens cleaning step as the number of pixels corresponding to foreign matter adhered to the lens increases.

Abstract: It is provided a state recognition system configured to recognize a state of a traveling road on which a vehicle travels, the state recognition system being configured to: select a substance adhered on a lens of a camera mounted on the vehicle in an image captured by the camera; and determine whether the traveling road is on-road or off-road by determining a type and an amount of the selected adhered substance.

Abstract: An in-vehicle surrounding environment recognition device includes: a photographic unit that photographs a road surface around a vehicle and acquires a photographic image; an application execution unit that recognizes another vehicle on the basis of the photographic image, and detects a relative speed of the other vehicle with respect to the vehicle; a reflection determination unit that, on the basis of the photographic image, determines upon presence or absence of a reflection of a background object from the road surface; a warning control unit that controls output of a warning signal on the basis of the result of recognition of the other vehicle; and a warning prevention adjustment unit that suppresses output of the warning signal on the basis of the relative speed of the other vehicle, if it has been determined that there is the reflection of the background object from the road surface.

Abstract: A three-dimensional object detection device has an image capturing unit, detection area setting unit, a three-dimensional object detection unit and a lens state assessment unit. The image capturing unit has a lens for capturing images behind a vehicle. The detection area setting unit sets a detection area behind the vehicle. The three-dimensional object detection unit detects a three-dimensional object that is present in the detection area based on the acquired images. The lens state assessment unit detects if the lens is in a wet state. When a determination is made by that the lens is in a wet state, the detection area setting unit changes a position of the detection area from a first detection area, which is first set as the detection area to a second detection area, in which a display area for a driving lane marker on a driving lane side of the vehicle is removed.

Abstract: A three-dimensional object detection device has a camera, a three-dimensional object detection unit, a lens cleaning device, a lens state assessment unit and a controller. The camera has a lens for forming an image of an area rearward of a vehicle. The three-dimensional object detection unit detects a three-dimensional object rearward of the vehicle based on the captured images. The lens cleaning device sprays cleaning fluid to clean the lens of the camera. The lens state assessment unit accesses whether the lens is in a predetermined state subject to control based on a timing at which cleaning fluid is sprayed on the lens. The controller suppresses detection of the three-dimensional object by retaining detection or assessment results for a predetermined length of time that were obtained immediately before the lens was assessed to be in the state subject to control, upon assessment that the lens state is subject to control.

Abstract: A three-dimensional object detection has an image capturing device, a three-dimensional object detection unit, a high-luminance area assessment unit and a controller. The image capturing device captures images of an area including a right-side detection area or a left-side detection area rearward of a vehicle. The three-dimensional object detection unit detects a three-dimensional object based on the images acquired by the image capturing device. The high-luminance area assessment unit accesses a first detection area including a high-luminance area complying with a predetermined reference on either the right-side detection area or the left-side detection area.

Abstract: A three-dimensional object detection device includes an image capturing unit, an image conversion unit, a three-dimensional object detection unit, a three-dimensional object assessment unit and a control unit. The image conversion unit converts images obtained by the image capturing unit to create bird's-eye view images. The three-dimensional object detection unit detects a presence of a three-dimensional object within a detection area based on differential waveform information or edge information. The stationary three-dimensional object assessment unit assesses whether the detected three-dimensional object is a shadow of a tree along a road traveled by the host vehicle. The three-dimensional object assessment unit assesses whether the three-dimensional object detected is a vehicle within the detection area.

Abstract: A three-dimensional object detection device includes an image capturing unit, an image conversion unit, a three-dimensional object detection unit, a three-dimensional object assessment unit and a control unit. The image conversion unit converts a viewpoint of the images obtained by the image capturing unit to create bird's-eye view images. The three-dimensional object detection unit detects a presence of a three-dimensional object within the predetermined detection area by vehicle width direction detection processing. The three-dimensional object assessment unit assesses whether the three-dimensional object detected is another vehicle that is present within the predetermined detection area.

Abstract: A three-dimensional object detection device includes an image capturing unit, an image conversion unit, a three-dimensional object detection unit, a movement speed calculation unit, a three-dimensional object assessment unit, a non-detection-object assessment unit and a control unit. The image conversion unit converts a viewpoint of the images to create bird's-eye view images. The three-dimensional object detection unit detects a presence of a three-dimensional object within the predetermined detection area based on difference waveform information. The movement speed calculation unit calculates a movement speed of the three-dimensional object. The non-detection-object assessment unit detect san amount of variability in the movement speed of the three-dimensional object, and assesses whether the three-dimensional object is a non-detection object based on the amount of variability.

Abstract: A three-dimensional object detection device includes an image capturing unit, an image conversion unit, a three-dimensional object detection unit and a light source detection unit. The image conversion unit converts a viewpoint of the images obtained by the image capturing unit to create bird's-eye view images. The three-dimensional object detection unit detects a presence of a three-dimensional object within the adjacent lane. The three-dimensional object detection unit determines the presence of the three-dimensional object within the adjacent lane-when the difference waveform information is at a threshold value or higher. The three-dimensional object detection unit set a threshold value lower so that the three-dimensional object is more readily detected in a rearward area than forward area with respect to a line connecting the light source and the image capturing unit.

Abstract: A three-dimensional object detection device includes an image capturing unit, an image conversion unit, a three-dimensional object detection unit, a light source detection unit and a control unit. The image conversion unit converts a viewpoint of the images obtained by the image capturing unit to create bird's-eye view images. The three-dimensional object detection unit detects a presence of a three-dimensional object within the adjacent lane. The three-dimensional object detection unit determines the presence of the three-dimensional object within the adjacent lane-when the difference waveform information is at a threshold value or higher. The control unit set a threshold value higher so that the three-dimensional object is more difficult to detect in a forward area than rearward area with respect to a line connecting the light source and the image capturing unit when the light source has been detected.

Abstract: A three-dimensional object detection device includes an image capturing unit, a detection area setting unit, an image conversion unit, a three-dimensional object detection unit, a reference image area setting unit, a contour information extraction unit, a reference sharpness calculation unit and a subject sharpness calculation unit. The image conversion unit converts a viewpoint of an image obtained by the image capturing unit to create a bird's-eye view image. The reference image area unit sets a reference image area for extracting contour information by the contour information extraction unit. The reference sharpness calculation unit calculates a reference sharpness using contour information of the reference image area. The subject sharpness calculation unit calculates a subject sharpness using contour information of the detection area.

Abstract: A three-dimensional object detection device can enhance the accuracy in detecting a three-dimensional object regardless of the brightness in the detection environment. The device has an image capture means that captures an image of a predetermined area and an image conversion means that converts the image through a viewpoint conversion into birds-eye view image. A first three-dimensional object detection means aligns positions of bird's-eye view images at different times obtained by the image conversion means, counts the number of pixels that exhibit a predetermined difference on a differential image of the aligned bird's-eye view images to generate a frequency distribution thereby creating differential waveform information, and detects a three-dimensional object on the basis of the differential waveform information.

Abstract: A three-dimensional object detection device includes an image capturing unit, an image conversion unit, a three-dimensional object detection unit, a light source detection unit a degree-of-certainty assessment unit and a control unit. The degree-of-certainty assessment unit assesses a degree of certainty that a light source is headlights of another vehicle in two lanes over. The control unit sets a threshold value so that the three-dimensional object is more difficult to detect in a forward area of a line connecting the light source and the image capturing unit in the detection frame when the degree of certainty is at a predetermined value or higher, and sets a threshold value so that the three-dimensional object is more difficult to detect in progression from a center side toward front or rear ends of the detection frame when the degree of certainty is less than a predetermined value.

Abstract: A periodic stationary object detection system extracts a feature point of a three-dimensional object from image data on a predetermined region of a bird's eye view image for each of multiple sub regions included in the predetermined region, calculates waveform data corresponding to a distribution of the feature points in the predetermined region on the bird's eye view image, and judges whether or not the three-dimensional object having the extracted feature point is a periodic stationary object candidate on the basis of whether or not peak information of the waveform data is equal to or larger than a predetermined threshold value.