Abstract: An image processing method for calculating feature amounts of a facial part in a face on the basis of a plurality of image data obtained in chronological order, comparing the calculated feature amounts with a threshold value, and recognizing the facial part, includes: calculating face orientations on the basis of image data; storing, in a storage, the feature amounts calculated from the image data, the feature amounts being associated with the face orientations; and recognizing a facial part in different image data of the face other than the plurality of the image data on the basis of a feature amount calculated from the different image data, the feature amounts stored in the storage associated with the face orientation in the different image data, and a threshold.

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: 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 processing method for calculating feature amounts of a facial part in a face on the basis of a plurality of image data obtained in chronological order, comparing the calculated feature amounts with a threshold value, and recognizing the facial part, includes: calculating face orientations on the basis of image data; storing, in a storage, the feature amounts calculated from the image data, the feature amounts being associated with the face orientations; and recognizing a facial part in different image data of the face other than the plurality of the image data on the basis of a feature amount calculated from the different image data, the feature amounts stored in the storage associated with the face orientation in the different image data, and a threshold.

Abstract: The CPU of a face orientation detection apparatus which acquires an image frame photographed by a camera through a cable detects the face region in the horizontal direction of the acquired image frame by executing computer programs stored on a hard disk. Moreover, the CPU detects the eye position in the vertical direction from the image frame, and detects the nose position in the horizontal direction based on the detected eye position. Furthermore, the CPU detects the orientation of the face included in the image frame, based on the detected nose position and face region.

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: 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: 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: 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: Obtaining an image frame picked up by a camera 2 through a cable C, a CPU 10 of a computer 1 identifies an eye area in the image frame and stores a template indicating the identified area as a tracking template. Moreover, the CPU 10 identifies an eye area in an image frame to be obtained subsequently on the basis of the tracking template, and calculates a correlation value between the template of the identified area and the tracking template. Furthermore, when the calculated correlation value is larger than a threshold stored in an HD 11 in advance, the CPU 10 stores the template indicating the identified area in the RAM 12 as a tracking template, so as to update an eye area in a series of two image frames in chronological order.

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: Obtaining an image frame picked up by a camera 2 through a cable C, a CPU 10 of a computer 1 identifies an eye area in the image frame and stores a template indicating the identified area as a tracking template. Moreover, the CPU 10 identifies an eye area in an image frame to be obtained subsequently on the basis of the tracking template, and calculates a correlation value between the template of the identified area and the tracking template. Furthermore, when the calculated correlation value is larger than a threshold stored in an HD 11 in advance, the CPU 10 stores the template indicating the identified area in the RAM 12 as a tracking template, so as to update an eye area in a series of two image frames in chronological order.

Abstract: The CPU of a face orientation detection apparatus which acquires an image frame photographed by a camera through a cable detects the face region in the horizontal direction of the acquired image frame by executing computer programs stored on a hard disk. Moreover, the CPU detects the eye position in the vertical direction from the image frame, and detects the nose position in the horizontal direction based on the detected eye position. Furthermore, the CPU detects the orientation of the face included in the image frame, based on the detected nose position and face region.