US 8,620,036 B2Granted

System and method for controlling image quality

AssigneeS1 Corporation

InventorsAnwar A. Irmatov, Dmitry Y. Buryak, Victor D. Kuznetsov, Wang-Jin Mun, Hae-Kwang Yang, Yong-Jin Lee

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Abstract

An image quality control system and method is disclosed. At least one infrared camera takes a screen image of a room. When there are a plurality of cameras, images of the cameras are synchronized with respect to time, and a specific object of the image is tracked to estimate image quality of the object. When there are a plurality of cameras, a 3D screen model is reconfigured, and positions of the cameras and the infrared lighting tools are controlled. Infrared lighting and the cameras are controlled, and particularly, optical axis direction, optical magnification, exposure time, and the iris of the camera can be amended. Next, a high-quality object image list can be generated so as to process the images.

Claims12

Dependent claims

A method for recognizing a face within an image, comprising:

performing facial recognition of an input image using a person recognition device, with operations including:
classifying a plurality of sample images into classes, images of the plurality of sample images respectively having information on a face of a target to be recognized according to classifications;
recording classifications of the plurality of sample images in a database;
estimating similarity between the input image and the sample images in the database based on an image classification algorithm for measuring similarity of two images and determining identification thereof;
determining a first class of the input image based on a result of the estimated similarity between the input image and the sample image;
performing verification for the facial recognition of the input image using a recognition result checking device, with operations including:
generating, for each particular class of the database, a binary classifier for identifying a face of a target of the particular class of the database, wherein the binary classifier includes a multiple vector having a similarity measurement value between the input image and a corresponding sample image in the particular class of the database, and wherein the binary classifier is used to identify classes of sample images in the database that are incorrectly identified by the person recognition device;
attempting to apply the binary classifier generated for each particular class of the database to the input image;
determining a second class of the input image based on a result of successfully applying a particular binary classifier;
and
combining the first and the second classes determined for the input image;
and
confirming the facial recognition of the input image based on a result of the combining the first and the second classes.

10 more elements

A device for recognizing a face in an image, comprising:

an image database storing a plurality of sample images having information on a face of a target to be recognized when each of the plurality of sample images are organized by class;
a similarity measurement device configured to measure similarity of an input image and the sample images of the image database based on an image classification algorithm measuring similarity of two images and determine identification thereof;
a person recognition device configured to determine a first class of the input image based on a result of measuring similarity, the person recognition device configured to perform operations that:
classify the plurality of sample images into classes, images of the plurality of sample images respectively having information on a face of a target to be recognized according to classifications;
record classifications of the plurality of sample images in the image database;
determine a first class of the input image based on a result of the estimated similarity between the input image and the sample image, using the similarity measurement device;
and
a recognition result checking device configured to attempt to apply a binary classifier for each class of the image database to identify a face of a target of a class and verify the first class of the input image, with operations that:
generate, for each particular class of the image database, the binary classifier,
wherein the binary classifier includes a multiple vector having a similarity measurement value between the input image and a corresponding sample image in the particular class of the database,
attempt to apply each binary classifier to the input image;
determine a second class of the input image based on a result of successfully applying a particular binary classifier;
combine the first and the second classes of the determined for the input image;
and
finally determine which class corresponds to the input image based on a result of combining;
wherein at least one of the above devices are implemented by at least one processor.

13 more elements

Dependencies are inferred from the claim text.