Denso Corporation

Nippon Soken, Inc.

Hiroki Nakano

Naoki Kawasaki

Tetsuya Takafuji

Katsuhiko Hibino

Kenta Hoki

An image analysis apparatus picks up an image of a region ahead of a vehicle using a camera, and allows a control unit to analyze picked-up image data generated by the camera to learn a focus-of-expansion position. The control unit controls the learning performance as follows. Specifically, the control unit does not start the learning performance for the focus-of-expansion position until a state where a detection value of a vehicle speed exceeds a reference speed exceeds a specified duration of time. When the state where a detection value of a vehicle speed exceeds a reference speed exceeds the specified duration of time, the learning performance for the focus-of-expansion position is started from this time point. The specified duration of time may be determined on the basis of statistics on the durations of simulated runs of the vehicle performed on a chassis dynamometer in a vehicle inspection.

Image analysis apparatus mounted to vehicle

In a boundary line recognition apparatus, a boundary line candidate extracting part extracts boundary line candidates from image data obtained by an on-vehicle camera based on known image processing such as pattern matching and Hough transform. One or more kinds of boundary line feature calculating parts calculate one or more likelihoods of each boundary line candidate. The likelihood indicates a degree of probability to be the boundary line. A boundary line feature combining means multiplies the likelihoods of each boundary line candidate and outputs a combined likelihood. A boundary line candidate selecting part selects the boundary line candidate having a maximum likelihood as the boundary line. The boundary line feature calculating part further calculates the likelihood of the boundary line candidate using a dispersion of brightness and an internal edge amount, and changes the likelihood based on an additional likelihood obtained by a driving lane surface feature extracting part.

Boundary line recognition apparatus

In a lane boundary detection device, a plurality of edge components are extracted from a captured image capturing the periphery of the own vehicle. Candidates of a curve (including straight lines) that is to be the boundary of a driving area are extracted as boundary candidates based on the placement of the plurality of edge components. Then, an angle formed by a tangent in a predetermined section of each extracted boundary candidate and a vertical line in the captured image is calculated. Boundary candidates of which the formed angle is less than an angle reference value are set to have low probability. The boundary candidate having the highest probability among the boundary candidates is set as the boundary of the driving area.

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Kariya, Japan

Hiroki Nakano