A method and apparatus for processing images. A set of candidate targets is identified in a first image and in a second image that corresponds with the first image. A set of first scores is generated for the set of candidate targets using the first image. A set of second scores is generated for the set of candidate targets using the second image. A set of final scores is computed for the set of candidate targets using the set of first scores and the set of second scores. A determination is made as to which of the set of candidate targets is a target of interest based on the set of final scores.

An image correction method, a terminal device and a non-transitory computer readable storage medium are provided. The method includes: extracting human face attributes of an image; acquiring, from target regions, a first region having a human face correction attribute; acquiring, from the target regions, a second region having a human face protection attribute; and performing image correction on the human face in the first region, and performing pixel compensation, according to background pixels of the image, on a blank region generated by the image correction in the first region.

An apparatus includes a display control unit, a receiving unit, an adjusting unit, and a determination unit. The display control unit is configured to display an image showing a result of detection of a defect from a captured image of a structure on a display device. The receiving unit is configured to receive an operation to specify part of the displayed image as a first region and an operation to give an instruction to correct at least part of the detection data corresponding to the first region. The adjusting unit is configured to adjust a parameter to be applied to the first region according to the instruction. The determination unit is configured to determine one or more second regions to which the adjusted parameter is to be applied from a plurality of segmented regions of the image.

When searching for a registered image similar to a query image, an image processing apparatus estimates an area having a difference by comparing images determined to be similar if a plurality of similar images is found at the time of search of a similar image using an image feature amount in order to enhance search accuracy. Then, the image processing apparatus compares the query image with the plurality of images similar to the query image based on the difference area.

The present disclosure relates to a target tracking method, device, system, and a non-transitory computer-readable storage medium. The method includes: determining an area where a current target is located by performing target detection on a current frame image; extracting a current position information of the area where the current target is located; predicting a position information of an area where each historical target is located at a corresponding moment of the current frame image based on historical position information of an area where each historical target is located in one or more historical frame images; determining a historical target that is the same target as the current target based on a position difference between the current position information and the predicted position information, and tracking the current target.

Techniques for selecting a digital image are disclosed. The techniques may include receiving a first set of digital images, analyzing the first set of digital images to extract first image features from each of the first set of digital images, accessing a user profile, comparing the extracted first image features to a preset list of image features, ranking each digital image of the first set, selecting each digital image having a ranking that exceeds a threshold, assigning a category to each selected digital image based on a comparison of each selected digital image to a category database of digital image categories, displaying each selected digital image with the assigned category, receiving an input from the user in response to the displaying, updating the user profile and the category database based on the input, and selecting at least one subsequent digital image based on the updated user profile and category database.

A method, including receiving a two-dimensional (2D) image of a three-dimensional (3D) object recorded at a first angle of rotation of the object, and identifying, in the 2D image, a set of image descriptors, each of the image descriptors including an image keypoint and one or more image features. The set of image descriptors are compared against sets of template descriptors for respective previously captured 2D images, each of the template descriptors comprising a template keypoint and one or more template features. Using a threshold, a given set of template descriptors matching the set of image descriptors are identified, the given set of template descriptors corresponding to a given previously captured 2D image of the 3D object recorded at a second angle of rotation of the object. Any of the image descriptors not in the given set of the template descriptors are added to the given set of template descriptors.

Devices, systems, and methods obtain a region of an image; generate known-object scores for the region using known-object detectors, wherein each known-object detector of the known-object detectors detects objects in a respective object class; determine a likelihood that the region includes a complete object; and determine a likelihood that the region includes an unknown object based on the likelihood that the region includes a complete object and on the known-object scores.

Embodiments of this disclosure provide a recognition method and apparatus for false detection of an abandoned object and an image processing device. The method includes: performing foreground detection on a current frame image, so as to obtain a foreground image of the current frame image, the foreground image comprising an abandoned object foreground image; clustering contours in the abandoned object foreground image into a group, and take the group as a candidate region of an abandoned object; and comparing the candidate region of the abandoned object with a reference background image, judging whether the candidate region of the abandoned object is matched with the reference background image, and a match, deeming that the abandoned object is false detection.

The present invention discloses a method for protecting specific information, comprising: receiving an image containing specific information; identifying boundaries of the image; matching the image with a predetermined image template based on the boundaries so as to determine a specific information region of the image; and performing predetermined processing on the specific information region of the image to be presented in response to determining the specific information region of the image, so as to protect the specific information. The method of the invention for protecting specific information can efficiently protect relevant specific information without identifying detailed semantic content in an image.