The image processing device includes an imaging unit that images a subject and a distance map acquisition unit that acquires information regarding a distance distribution of the subject as map data. The distance map acquisition unit acquires map data with an image deviation amount or a defocused amount related to a captured image or distance map data in conformity with a TOF scheme or an imaging plane phase difference detection scheme of using a pupil division type image sensor. An image processing unit generates data of a texture image in which a low-frequency component of a captured image is inhibited and combines the data of the texture image and the map data acquired by the distance map acquisition unit to generate image data in which a distance distribution of a subject is expressed.

The image processing device includes an imaging unit that images a subject and a distance map acquisition unit that acquires information regarding a distance distribution of the subject as map data. The distance map acquisition unit acquires map data with an image deviation amount or a defocused amount related to a captured image or distance map data in conformity with a TOF scheme or an imaging plane phase difference detection scheme of using a pupil division type image sensor. An image processing unit generates data of a texture image in which a low-frequency component of a captured image is inhibited and combines the data of the texture image and the map data acquired by the distance map acquisition unit to generate image data in which a distance distribution of a subject is expressed.

An electronic device is disclosed. The present electronic device comprises a display, a processor electrically connected with the display so as to control the display, and a memory electrically connected with the processor, wherein the memory includes at least one command, and the processor, by executing at least one command, acquires a plurality of object images corresponding to a plurality of objects in a two-dimensional image, acquires a plurality of three-dimensional modeling images corresponding to the plurality of object images and information related to the plurality of objects by applying the plurality of object images to a plurality of network models, and displays, on the display, the three-dimensional images including the plurality of three-dimensional modeling images on the basis of the information related to the plurality of objects and the location information about the plurality of objects in the two-dimensional image.

An image processing apparatus comprises: an obtaining unit configured to obtain an image and distance information concerning a distance from an in-focus plane, which corresponds to each pixel included in the image; a setting unit configured to set an image processing condition according to the distance information based on an output characteristic of an output apparatus concerning a sharpness; and a processing unit configured to perform image processing for the image using the distance information obtained by the obtaining unit and the image processing condition set by the setting unit, wherein the processing unit changes, in accordance with the distance information, a band of a spatial frequency of the image to which the image processing is applied.

An image processing apparatus comprises: an obtaining unit configured to obtain an image and distance information concerning a distance from an in-focus plane, which corresponds to each pixel included in the image; a setting unit configured to set an image processing condition according to the distance information based on an output characteristic of an output apparatus concerning a sharpness; and a processing unit configured to perform image processing for the image using the distance information obtained by the obtaining unit and the image processing condition set by the setting unit, wherein the processing unit changes, in accordance with the distance information, a band of a spatial frequency of the image to which the image processing is applied.

Methods and systems for determining information for a specimen are provided. Certain embodiments relate to bump height 3D inspection and metrology using deep learning artificial intelligence. For example, one embodiment includes a deep learning (DL) model configured for predicting height of one or more 3D structures formed on a specimen based on one or more images of the specimen generated by an imaging subsystem. One or more computer systems are configured for determining information for the specimen based on the predicted height. Determining the information may include, for example, determining if any of the 3D structures are defective based on the predicted height. In another example, the information determined for the specimen may include an average height metric for the one or more 3D structures.

Contactless fingerprint reader. The contactless fingerprint reader has one or more light sources adapted to emit light under different lighting conditions, a first camera adapted to successively capture first images of a subject captured with and without flash light, at least one second camera adapted to capture second images from different angles, one or more sensors adapted to generate one or more spatial-temporal signals representing a change of a distance between said subject and one or more locations of the contactless fingerprint reader, and communication module for sending the first images, said second images, and the one or more spatial-temporal signals to an anti-spoofing device.

Contactless fingerprint reader. The contactless fingerprint reader has one or more light sources adapted to emit light under different lighting conditions, a first camera adapted to successively capture first images of a subject captured with and without flash light, at least one second camera adapted to capture second images from different angles, one or more sensors adapted to generate one or more spatial-temporal signals representing a change of a distance between said subject and one or more locations of the contactless fingerprint reader, and communication module for sending the first images, said second images, and the one or more spatial-temporal signals to an anti-spoofing device.

Embodiments of the present application provide image processing methods and apparatus. A image processing method disclosed herein comprises: acquiring, from an image, two regions which have a textural similarity higher than a first value and have different depths; performing frequency-domain conversion on each of the regions, to obtain a frequency-domain signal of each region; and optimizing the image at least according to the frequency-domain signal of each region, the depth of each region and a focusing distance of the image.

Embodiments of the present application provide image processing methods and apparatus. A image processing method disclosed herein comprises: acquiring, from an image, two regions which have a textural similarity higher than a first value and have different depths; performing frequency-domain conversion on each of the regions, to obtain a frequency-domain signal of each region; and optimizing the image at least according to the frequency-domain signal of each region, the depth of each region and a focusing distance of the image.