Abstract: A fingerprint recognition method and apparatus are applied to the field of fingerprint recognition technologies. The method includes: collecting a to-be-enrolled fingerprint image; performing, based on a first calibration image, calibration processing on the to-be-enrolled fingerprint image to obtain a first fingerprint image; and determining whether an adaptive calibration image exists; and updating the first calibration image based on the first fingerprint image and a first update coefficient when the adaptive calibration image exists, to obtain a second calibration image; or generating a third calibration image based on the first fingerprint image when no adaptive calibration image exists. The third calibration image is an image obtained by performing summation and averaging on a plurality of frames of fingerprint images, or the third calibration image is an image obtained by updating the first calibration image based on the first fingerprint image.

Abstract: A fingerprint recognition method and apparatus are provided. The method is applied to the field of fingerprint recognition technologies. The method includes: when a first fingerprint image is successfully matched, judging whether matching information of the first fingerprint image satisfies a first preset condition; when the matching information of the first fingerprint image satisfies the first preset condition, judging whether a cumulative update count of a second fingerprint template is greater than a first quantity threshold; when the cumulative update count of the second fingerprint template is greater than the first quantity threshold, judging whether priority information of the second fingerprint template satisfies a second preset condition; and when the priority information of the second fingerprint template satisfies the second preset condition, updating the second fingerprint template with the first fingerprint image.

Abstract: The method includes: obtaining features of L key points of a first fingerprint image; determining G pairs of key points based on the L key points of the first fingerprint image and L key points of a first fingerprint template; sorting the G pairs of key points based on the first distance parameter corresponding to each pair of key points, and determining N pairs of key points from the G pairs of key points that are sorted; determining a first rotation matrix using the N pairs of key points, and rotating the first fingerprint image based on the first rotation matrix to obtain a second fingerprint image, where the second fingerprint image is in a same direction as the first fingerprint template; and performing similarity matching using the second fingerprint image and the first fingerprint template.

Abstract: A fingerprint recognition method and apparatus are provided. The method is applied to the field of fingerprint recognition technologies. The method includes: when a first fingerprint image is successfully matched, judging whether matching information of the first fingerprint image satisfies a first preset condition; when the matching information of the first fingerprint image satisfies the first preset condition, judging whether a cumulative update count of a second fingerprint template is greater than a first quantity threshold; when the cumulative update count of the second fingerprint template is greater than the first quantity threshold, judging whether priority information of the second fingerprint template satisfies a second preset condition; and when the priority information of the second fingerprint template satisfies the second preset condition, updating the second fingerprint template with the first fingerprint image.

Abstract: A fingerprint recognition method and apparatus are applied to the field of fingerprint recognition technologies. The method includes: collecting a to-be-enrolled fingerprint image; performing, based on a first calibration image, calibration processing on the to-be-enrolled fingerprint image to obtain a first fingerprint image; and determining whether an adaptive calibration image exists; and updating the first calibration image based on the first fingerprint image and a first update coefficient when the adaptive calibration image exists, to obtain a second calibration image; or generating a third calibration image based on the first fingerprint image when no adaptive calibration image exists. The third calibration image is an image obtained by performing summation and averaging on a plurality of frames of fingerprint images, or the third calibration image is an image obtained by updating the first calibration image based on the first fingerprint image.

Abstract: Provided are a sample analyzer and a sample analysis method. The sample analyzer includes: a sampling apparatus configured to collect a blood sample; a sample preparation apparatus configured to mix the blood sample with a hemolytic agent and a dye to prepare a test sample liquid; an optical detection apparatus configured to detect side-scattered light signals and fluorescence signals generated by particles in the test sample liquid; and a processor configured to: generate a scatter diagram based on at least the side-scattered light signals and the fluorescence signals, and obtain a predetermined feature region, wherein an intensity of side-scattered light corresponding to a central position of the predetermined feature region is greater than an intensity of side-scattered light corresponding to a central position of a region containing neutrophil granulocyte population; and obtain a blast cell parameter based on the predetermined feature region.

Abstract: The method includes: obtaining features of L key points of a first fingerprint image; determining G pairs of key points based on the L key points of the first fingerprint image and L key points of a first fingerprint template; sorting the G pairs of key points based on the first distance parameter corresponding to each pair of key points, and determining N pairs of key points from the G pairs of key points that are sorted; determining a first rotation matrix using the N pairs of key points, and rotating the first fingerprint image based on the first rotation matrix to obtain a second fingerprint image, where the second fingerprint image is in a same direction as the first fingerprint template; and performing similarity matching using the second fingerprint image and the first fingerprint template.

Abstract: Provided are a sample analyzer and a sample analysis method. The sample analyzer includes: a sampling apparatus configured to collect a blood sample; a sample preparation apparatus configured to mix the blood sample with a hemolytic agent and a dye to prepare a test sample liquid; an optical detection apparatus configured to detect side-scattered light signals and fluorescence signals generated by particles in the test sample liquid; and a processor configured to: generate a scatter diagram based on at least the side-scattered light signals and the fluorescence signals, and obtain a predetermined feature region, wherein an intensity of side-scattered light corresponding to a central position of the predetermined feature region is greater than an intensity of side-scattered light corresponding to a central position of a region containing neutrophil granulocyte population; and obtain a blast cell parameter based on the predetermined feature region.