Abstract: Provided are an image processing method, an image processing system, an image processing device and a computer program for detecting a detection object such as nares of the driver with a high degree of accuracy in, for example, a system using an in-vehicle camera which is mounted on a vehicle and takes an image of the face of the driver. A detection object is diversified by a variety of detection methods such as a method for detecting a plurality of locations in the vertical direction as candidates during image pickup of an image, detecting a range to be a candidate of a detection object on the basis of the brightness of a pixel for each of rows of pixels lined up in the horizontal direction corresponding to each detected location and specifying a detection object from candidates of a detection object on the basis of the length of the detected range.

Abstract: A system using an in-vehicle camera mounted on a vehicle for an image pickup object of the face of the driver, for: continuously taking an image of the image pickup object; performing manipulation, such as enlargement of an area including the image pickup object with a reference point being the center, for a second image based on image pickup after a first image, on the basis of the range of the image pickup object detected from the first image, the width of the facial contour of the driver, for example, and also a reference point such as the center of the face to be decided based on the location of the eyes and nose of the driver; and performing image processing, such as detection of the range of the image pickup object and decision of the reference point, for the manipulated second image.

Abstract: An image recognition device for generating an output rotation image from input original image data, including a memory section being capable of storing data of a line including pixels of the original image data to be processed, an angle-to-sine/cosine converting section obtaining an X component and a Y component where a pixel interval of the original image data is an oblique side based on a rotating angle, and a coordinate searching section calculating a reference coordinate of the output rotation image for the original image using the X component and the Y component in order of input of the original image data and outputting data of the output rotation image based upon the reference coordinate.

Abstract: Using an on-vehicle camera mounted on a vehicle to view the face of a driver as an imaging object, an image processing system judges the presence/absence of the imaging object in the image. An average luminance of an image when light of a particular wavelength is irradiated in an imaging direction is compared to an average luminance of an image imaged when no light is irradiated. When the difference between the average luminance values is equal to a reference value or less, it is judged that the imaging object is absent in the image by imaging.

Abstract: For example, a plurality of elliptical candidate areas that become candidate areas of detecting objects are set in an image, characteristic values such as average values of luminance of the pixels inside and outside the set candidate areas are compared, and a candidate area whose difference of the characteristic values is determined to be the maximum is detected as the area of the detecting object. In addition, central moment of the detecting object is calculated, and the inclination of the detecting object in the image is detected based on the calculated central moment. Further, two specific points such as eyes of the driver included in the detecting object are detected, and the inclination of the detecting object in the image determined by the detected two points is detected.

Abstract: There are provided an image processing method, and an image processing system, an image processing device, and a computer program product capable of detecting a position of a fringe portion of a detecting object such as an outline of a face of a driver with high precision, even when a variation of illuminance occurs locally in a system using, for example, an on-vehicle camera mounted on a vehicle for imaging the face of the driver. Luminance of pixels arranged in a first direction such as a horizontal direction of an image is subjected to quadric differential, and data based on a quadratic differentiation result is accumulated in a second direction such as a vertical direction, and based on an accumulated result, a position in the first direction of the detecting object in the image is detected.

Abstract: An image recognition device for generating an output rotation image from input original image data, including a memory section being capable of storing data of a line including pixels of the original image data to be processed, an angle-to-sine/cosine converting section obtaining an X component and a Y component where a pixel interval of the original image data is an oblique side based on a rotating angle, and a coordinate searching section calculating a reference coordinate of the output rotation image for the original image using the X component and the Y component in order of input of the original image data and outputting data of the output rotation image based upon the reference coordinate.

Abstract: Provided are an image processing method, an image processing system, an image processing device and a computer program for detecting a detection object such as nares of the driver with a high degree of accuracy in, for example, a system using an in-vehicle camera which is mounted on a vehicle and takes an image of the face of the driver. A detection object is diversified by a variety of detection methods such as a method for detecting a plurality of locations in the vertical direction as candidates during image pickup of an image, detecting a range to be a candidate of a detection object on the basis of the brightness of a pixel for each of rows of pixels lined up in the horizontal direction corresponding to each detected location and specifying a detection object from candidates of a detection object on the basis of the length of the detected range.

Abstract: For example, a plurality of elliptical candidate areas that become candidate areas of detecting objects are set in an image, characteristic values such as average values of luminance of the pixels inside and outside the set candidate areas are compared, and a candidate area whose difference of the characteristic values is determined to be the maximum is detected as the area of the detecting object. In addition, central moment of the detecting object is calculated, and the inclination of the detecting object in the image is detected based on the calculated central moment. Further, two specific points such as eyes of the driver included in the detecting object are detected, and the inclination of the detecting object in the image determined by the detected two points is detected.

Abstract: Using an on-vehicle camera mounted on a vehicle to view the face of a driver as an imaging object, an image processing system judges the presence/absence of the imaging object in the image. An average luminance of an image when light of a particular wavelength is irradiated in an imaging direction is compared to an average luminance of an image imaged when no light is irradiated. When the difference between the average luminance values is equal to a reference value or less, it is judged that the imaging object is absent in the image by imaging.

Abstract: There are provided an image processing method, and an image processing system, an image processor, and a computer program in which the fringe position of a detection object, e.g. the width of outline of the face of a driver, can be detected with high precision even when illuminance varies locally in a system employing a on-vehicle camera for imaging the face of the driver. Luminance of pixels arranged in the first direction of an image, e.g. the horizontal direction, is subjected to quadric differential, data based on the results of quadratic differential is integrated in the second direction, e.g. the vertical direction, and the position in the first direction of the detection object in the image is detected based on the integration results.

Abstract: A system using an in-vehicle camera mounted on a vehicle for an image pickup object of the face of the driver, for: continuously taking an image of the image pickup object; performing manipulation, such as enlargement of an area including the image pickup object with a reference point being the center, for a second image based on image pickup after a first image, on the basis of the range of the image pickup object detected from the first image, the width of the facial contour of the driver, for example, and also a reference point such as the center of the face to be decided based on the location of the eyes and nose of the driver; and performing image processing, such as detection of the range of the image pickup object and decision of the reference point, for the manipulated second image.

Abstract: An alarm system includes a miniature camera (10), a loudspeaker (20), a vehicle speed sensor (30), a longitudinal G sensor (40), a lateral G sensor (50) and an on-vehicle unit (60). A CPU (60a) of the on-vehicle unit (60) executes respective programs (61)–(64) in a ROM (60h), thereby outputting, if a traveling distance during a period for which a driver D continues to take an abnormal behavior exceeds a predetermined value when a traveling state of an automobile is kept stable, an alarm corresponding to a magnitude of the excess over the predetermined value from the loudspeaker (20). The alarm system is thus configured and is therefore capable of exactly outputting the alarm when a danger actually rises.

Abstract: A vehicle-mounted image processor in which image analysis for judging the possibility of a danger, e.g., crash, can be carried out accurately even when the speed of a vehicle is high. The vehicle-mounted image processor comprises a means for storing a specified volume of image data delivered from a vehicle-mounted camera, a means performing image analysis only of the image data in a specified range of the latest image data stored in the image data storage means, and a processing object control means for allowing the image analysis means to grasp the moving speed of the vehicle, to specify an object being processed such that the size and the position thereof has a negative correlation with the moving speed of the vehicle in the image data stored in the image data storage means, and to perform image analysis on the image data in the specified range.

Abstract: An alarm system includes a miniature camera (10), a loudspeaker (20), a vehicle speed sensor (30), a longitudinal G sensor (40), a lateral G sensor (50) and an on-vehicle unit (60). A CPU (60a) of the on-vehicle unit (60) executes respective programs (61)-(64) in a ROM (60h), thereby outputting, if a traveling distance during a period for which a driver D continues to take an abnormal behavior exceeds a predetermined value when a traveling state of an automobile is kept stable, an alarm corresponding to a magnitude of the excess over the predetermined value from the loudspeaker (20). The alarm system is thus configured and is therefore capable of exactly outputting the alarm when a danger actually rises.

Abstract: An image sensor section and a millimeter-wave sensor section separately detect objects. A sensor matching section determines whether the objects detected by the image sensor section and the millimeter-wave sensor section are one and the same object. If the objects are one and the same object, the sensor matching section estimates a position of the obstacle after a certain period. A collision prediction section determined whether there is going to be a collision between the vehicle and the object 50 from the position estimated by the sensor matching section.

Abstract: An image sensor section and a millimeter-wave sensor section separately detect objects. A sensor matching section determines whether the objects detected by the image sensor section and the millimeter-wave sensor section are one and the same object. If the objects are one and the same object, the sensor matching section estimates a position of the obstacle after a certain period. A collision prediction section determined whether there is going to be a collision between the vehicle and the object 50 from the position estimated by the sensor matching section.