A system segments a set of images of a property to identify a type of damage to the property. The system receives, from an image capturing device, a digital image of a roof or other feature of the property. The system processes the image to identify a set of segments, in which each segment corresponds to a piece of the feature, such as a tab or tooth of a shingle on the roof. The system saves a result of the processing to a data file as a segmented image of the property, and it uses the segmented image to identify a type of damage to the property.

An Internet of Thing (IoT) device includes a body with a processor, a camera and a wireless transceiver coupled to the processor.

A distortion correction component of a mobile device receives an image of a spread open multi-page document, determines a binding edge line of the spread open multi-page document, determines a first set of substantially vertical straight lines lying left of the binding edge line and a second set of substantially vertical straight lines lying right of the binding edge line. The distortion correction component then determines a first vanishing point based on the first set of substantially vertical straight lines and a second vanishing point based on the second set of substantially vertical straight lines. A first quadrangle is determined based on the first vanishing point and a second quadrangle is determined based on the second vanishing point. A corrected image for the first page is generated based on the first quadrangle and a corrected image for the second page is generated based on the second quadrangle.

An image matching apparatus matching a first image against a second image includes an acquiring unit, a generating unit, and a determining unit. The acquiring unit acquires a frequency feature of the first image and a frequency feature of the second image. The generating unit synthesizes the frequency feature of the first image and the frequency feature of the second image, and generates a quantized synthesized frequency feature in which a value of an element is represented by a binary value or a ternary value. The determining unit calculates a score indicating a degree to which the quantized synthesized frequency feature is a square wave having a single period, and matches the first image against the second image based on the score.

Computer-implemented methods and systems are provided for managing one or more images. An example method for indexing involves operating a processor to, divide an image portion of an image of the one or more images into a plurality of patches, for each patch of the image: detect one or more features of the patch; and assign the patch to at least one cluster of a plurality of clusters of the image, based on the one or more features of the patch. The processor is operable to, for each cluster of the image, select at least one patch from the cluster as at least one representative patch for the cluster; for each representative patch, generate an encoded representation based on one or more features of the representative patch; and generate an index identifier for the image based on the encoded representations of the representative patches of the image.

An image matching apparatus according to the present invention includes: a common region specification unit configured to specify a common region between a first image and a second image; a date replacement unit configured to generate a first replaced image in which a brightness value of the common region of the first image is replaced based on a pixel in the first image, and a second replaced image in which a brightness value of the common region of the second image is replaced based on a pixel in the second image; and a matching unit configured to perform matching between the first image and the second image based on frequency characteristics of the first replaced image and the second replaced image.

An object tracking integration method and an integrating apparatus are provided. In the method, one or more first images and one or more second images are obtained. The first image is captured from a first capturing apparatus, and the second image is captured from a second capturing apparatus. One or more target objects in the first image and in the second image are detected. A detection result of the target object in the first image and a detection result of the target object in the second image are matched. The detection result of the target object is updated according to a matching result between the detection results of the first image and the second image. Accordingly, the accuracy of the association and the monitoring range may be improved.

A method for feature tracking, image matching, using key point detection and a unique approach for associated key patch frequency domain descriptors. The system includes at least one processor and one or more computer storage media storing computer executable instructions that, when executed by the processor, cause the system to perform various operations. In particular, the system identifies a plurality of patches from a first image, detects one or more key points and associated patches from the plurality of patches, generates a set of transformed patches by transforming the key patches from the spatial domain to the frequency domain using a Discrete Cosine Transform or Discrete Fourier transform, encodes a set of illumination, rotational, scale and other geometric transformations of the transformed patches into a frequency descriptor, and matches a second image to the first image using the descriptors.

An image matching apparatus according to the present invention includes: a common region specification unit configured to specify a common region between a first image and a second image; a date replacement unit configured to generate a first replaced image in which a brightness value of the common region of the first image is replaced based on a pixel in the first image, and a second replaced image in which a brightness value of the common region of the second image is replaced based on a pixel in the second image; and a matching unit configured to perform matching between the first image and the second image based on frequency characteristics of the first replaced image and the second replaced image.

A system in a vehicle includes an image sensor to obtain images in an image sensor coordinate system and a depth sensor to obtain point clouds in a depth sensor coordinate system. Processing circuitry implements a neural network to determine a validation state of a transformation matrix that transforms the point clouds in the depth sensor coordinate system to transformed point clouds in the image sensor coordinate system. The transformation matrix includes rotation parameters and translation parameters.