A body and hand association method includes: an image to be detected of which an image content includes a body and a hand is acquired; a body bounding box of the body and a hand bounding box of the hand are determined in the image to be detected; an association probability between the body bounding box and the hand bounding box is determined; a circumscribed box of the body bounding box and the hand bounding box is determined; and a degree of association between the body and hand in the circumscribed box is determined based on a hand key point in the circumscribed box and the association probability.

A system for quantitively determining quality for pavement markings disposed along pavement on a roadway includes one or more controllers in wireless communication with a plurality of vehicles. The one or more controllers receive image data represents the pavement markings disposed along the pavement collected by the plurality of vehicles. The one or more controllers execute instructions to determine at least one of a color distance measurement between a mean color space value of the pavement markings and an ideal marking color space value and a marking intensity contrast ratio between the pavement markings and the pavement.

A system for quantitively determining quality for pavement markings disposed along pavement on a roadway includes one or more controllers in wireless communication with a plurality of vehicles. The one or more controllers receive image data represents the pavement markings disposed along the pavement collected by the plurality of vehicles. The one or more controllers execute instructions to determine at least one of a color distance measurement between a mean color space value of the pavement markings and an ideal marking color space value and a marking intensity contrast ratio between the pavement markings and the pavement.

An image processing method includes obtaining a sensed image, wherein the sensed image comprises a pattern; dividing the sensed image into a plurality of blocks; calculating a direction field according to the pattern in each of the blocks; calculating a similarity degree between the direction field of a first block and the direction fields of adjacent blocks of the first block; and classifying the first block into a first part according to the similarity degree of the first block.

The present invention relates to a method for acquiring an object information, the method comprising: obtaining an input image acquired by capturing a sea; obtaining a noise level of the input image; when the noise level indicates a noise lower than a predetermined level, acquiring an object information related to an obstacle included in the input image from the input image by using a first artificial neural network, and when the noise level indicates a noise higher than the predetermined level, obtaining a noise-reduced image of which the environmental noise is reduced from the input image by using a second artificial neural network, and acquiring an object information related to an obstacle included in the sea from the noise-reduced image by using the first artificial neural network.

The present invention relates to a method for acquiring an object information, the method comprising: obtaining an input image acquired by capturing a sea; obtaining a noise level of the input image; when the noise level indicates a noise lower than a predetermined level, acquiring an object information related to an obstacle included in the input image from the input image by using a first artificial neural network, and when the noise level indicates a noise higher than the predetermined level, obtaining a noise-reduced image of which the environmental noise is reduced from the input image by using a second artificial neural network, and acquiring an object information related to an obstacle included in the sea from the noise-reduced image by using the first artificial neural network.

A vision system (10) for a motor vehicle comprises an imaging apparatus (11) adapted to capture images from a surrounding of the motor vehicle, and a data processing unit (14) adapted to perform image processing on images captured by said imaging apparatus (11) in order to detect objects in the surrounding of the motor vehicle. The data processing unit (14) comprises a flicker mitigation software module (33) adapted to generate a flicker mitigated current image (30′) for a current image frame by filter processing involving a captured current image (30.sub.N+1) corresponding to the current image frame and at least one captured earlier image (30.sub.N) corresponding to an earlier image frame.

A vision system (10) for a motor vehicle comprises an imaging apparatus (11) adapted to capture images from a surrounding of the motor vehicle, and a data processing unit (14) adapted to perform image processing on images captured by said imaging apparatus (11) in order to detect objects in the surrounding of the motor vehicle. The data processing unit (14) comprises a flicker mitigation software module (33) adapted to generate a flicker mitigated current image (30′) for a current image frame by filter processing involving a captured current image (30.sub.N+1) corresponding to the current image frame and at least one captured earlier image (30.sub.N) corresponding to an earlier image frame.

A system and method for field extraction including determining a key position of a key in an electronic file, isolating candidate key values based on a distance from the key position, selecting a key value from the candidate key values based on an output of a trained neural network, and extracting the key and the key value from the electronic file, regardless of a key-value structure.

A system and method for field extraction including determining a key position of a key in an electronic file, isolating candidate key values based on a distance from the key position, selecting a key value from the candidate key values based on an output of a trained neural network, and extracting the key and the key value from the electronic file, regardless of a key-value structure.