Abstract:
A monitoring apparatus is provided. When a determination process of determining whether or not the part of an object located in a search range is an airborne substance, a rangefinder measures a distance to the object located in the search range for each of a plurality of unit areas forming the search range, a variation measure calculator calculates a variance of the distances (individual distances) measured for the respective unit areas, a variable threshold setter variably sets a variation measure threshold based on the individual distances, and a determiner determines that at least part of the object is an airborne substance if the calculated variance exceeds the variation measure threshold.
Abstract:
This invention is provided with: a camera for capturing the image of a travel path; an edge point extraction unit for extracting edge points on the basis of the brightness of an image captured by the camera; a candidate line extraction unit for extracting, on the basis of the succession of the extracted edge points, a candidate line for a boundary line demarcating the travel path; a frequency calculation unit for calculating, on the basis of edge points belonging to the candidate line extracted by the candidate line extraction unit, the frequency distribution of the edge points for a parameter that specifies the width of the boundary line; a probability generation unit for calculating, on the basis of the frequency distribution calculated by the frequency calculation unit, the distribution for the probability that the candidate line at the parameter is the boundary line; and a boundary line recognition unit for recognizing the boundary line on the basis of the probability distribution calculated by the probability generation unit.
Abstract:
A distance detection device calculates a pixel cost, every reference pixel, based on a difference between reference pixel information in a reference image and comparative pixel information in a comparative image while switching the reference and comparative images. The device calculates a parallax cost, every reference pixel, representing a cost regarding a change-amount of the parallax as a coordinate difference between a reference pixel and a comparative pixel when the reference image is switched. The device calculates a combination of each reference pixel and a comparative pixel having a minimum total cost every reference pixel. The minimum total cost represents a sum of the pixel cost and the parallax cost. The device obtains a relationship of a corresponding point between each reference pixel and its corresponding comparative pixel, and calculates a distance to an object in each captured image based on the relationship of the corresponding point.
Abstract:
In an image processing apparatus, an image acquiring unit acquires a first image and a second image that form stereoscopic images. A first sub-image extracting unit extracts first sub-images from the first image. A second sub-image extracting unit extracts second sub-images from the second image. A matching unit matches each pair of the first and second sub-images to determine a degree of similarity therebetween. A similar sub-image setting unit sets the second sub-image having a highest degree of similarity to the first sub-image to be a similar sub-image to the first sub-image. A brightness comparing unit compares in brightness each pair of the first and second sub-images. The matching unit is configured to, if a result of comparison made by the brightness comparing unit between a pair of the first and second sub-images is out of a predetermined brightness range, exclude such a pair of the first and second sub-images.
Abstract:
A traffic lane marking recognition apparatus includes a candidate detecting unit, a gap detecting unit, and a recognition reducing unit. The candidate detecting unit detects a lane dividing line candidate which is a candidate for a lane dividing line that defines a traffic lane on a road, based on an image of the road captured by an on-board camera that is mounted in a vehicle. The gap detecting unit detects a gap included in the lane dividing line candidate detected by the candidate detecting unit. When the gap is detected by the gap detecting unit, the recognition reducing unit reduces a probability of recognition of the lane dividing line candidate as a lane dividing line to a first probability that is lower than the probability when the gap detecting unit does not detect the gap, in a region from the gap closest to the vehicle towards a direction away from the vehicle.
Abstract:
In vehicle-lane boundary line detection, low-luminance values are acquired from areas corresponding to below a tire and directly below a vehicle center based on a road surface image. A snow rut degree is calculated based on a luminance ration between the areas. A probability is calculated from a map based on the calculated snow rut degree. A parameter indicating the degree of snow rut likeness is calculated by a low-pass filtering process. A snow rut determination is made by the calculation result being compared with a predetermined threshold. A final determination of whether or not a snow rut is present is made, with reference to an outside temperature. When determined that a snow rut is present, a determination is made not to perform the detection. When determined that a snow rut is not present, a determination is made to perform the detection.
Abstract:
A distance detection device calculates a pixel cost, every reference pixel, based on a difference between reference pixel information in a reference image and comparative pixel information in a comparative image while switching the reference and comparative images. The device calculates a parallax cost, every reference pixel, representing a cost regarding a change-amount of the parallax as a coordinate difference between a reference pixel and a comparative pixel when the reference image is switched. The device calculates a combination of each reference pixel and a comparative pixel having a minimum total cost every reference pixel. The minimum total cost represents a sum of the pixel cost and the parallax cost. The device obtains a relationship of a corresponding point between each reference pixel and its corresponding comparative pixel, and calculates a distance to an object in each captured image based on the relationship of the corresponding point.
Abstract:
A range correction device includes an image acquiring unit, a collimating unit, a disparity calculating unit, and an updating unit. The image acquiring unit acquires stereo images formed of a plurality of simultaneously captured images. The collimating unit collimates the stereo images acquired by the image acquiring unit, using a correction parameter for correcting a vertical displacement between stereo images. The disparity calculating unit calculates a distribution of horizontal disparities between the stereo images from the stereo images collimated by the collimating unit. The updating unit calculates a distribution of vertical displacements between the stereo images on the basis of the stereo images and the distribution of horizontal disparities calculated by the disparity calculating unit and updates the correction parameter on the basis of the distribution of the calculated vertical displacements.
Abstract:
A parallax detection device receives right side image and a left side image, makes right and left low resolution images, and divides the right low resolution image into blocks composed of pixels. For every block, the device detects a parallax of the block by searching the block in the left low resolution image having the region the same as the region of the block of the right low resolution image by using a dynamic programming method. The device divides the right side image into blocks, and searches a resolution corresponding block in the left side image having the region the same as the region of the block for every block by using a block matching method to detect a parallax of the block. The device limits the searching range of the resolution corresponding block in the left side image based on the parallax detection result obtained by the dynamic programming method.
Abstract:
A traffic lane marking recognition apparatus includes a candidate detecting unit, a gap detecting unit, and a recognition reducing unit. The candidate detecting unit detects a lane dividing line candidate which is a candidate for a lane dividing line that defines a traffic lane on a road, based on an image of the road captured by an on-board camera that is mounted in a vehicle. The gap detecting unit detects a gap included in the lane dividing line candidate detected by the candidate detecting unit. When the gap is detected by the gap detecting unit, the recognition reducing unit reduces a probability of recognition of the lane dividing line candidate as a lane dividing line to a first probability that is lower than the probability when the gap detecting unit does not detect the gap, in a region from the gap closest to the vehicle towards a direction away from the vehicle.