CPC G06V 20/176 (2022.01) [G06Q 40/08 (2013.01); G06Q 50/16 (2013.01); G06T 7/0002 (2013.01); G06V 10/25 (2022.01); G06V 10/26 (2022.01); G06V 10/54 (2022.01); G06V 10/56 (2022.01); G06V 10/82 (2022.01); G06T 2207/20084 (2013.01); G06V 20/17 (2022.01)] | 20 Claims |
1. A computer-implemented method of analyzing image data to automatically assess hail damage to a property, the method comprising:
accessing digital image data depicting a roof of the property;
segmenting, by a processor, the digital image data into a set of digital images depicting portions of the roof;
identifying, by the processor and using a convolutional neural network (CNN), regions of potential hail damage depicted in the set of digital images;
identifying, by the processor, features indicative of the potential hail damage and illustrated within the respective regions based at least in part on a numerical proximity of aspect ratios of the features to one, wherein identifying the features comprises:
determining sections of a digital image from the set of digital images, the sections including a first section within a region of potential hail damage and a second section outside of the region of potential hail damage; and
identifying a texture feature within the sections by performing a Gray-Level Co-Occurrence Matrices (GLCM) analysis on the sections to output a set of statistical properties comprising one or more of contrast, entropy, energy, or homogeneity for the first section and the second section; and
generating, by the processor, using a classification model, and based on the features, an output indicating a presence of hail damage associated with the roof, wherein the output is used to automatically determine an estimated damage amount to the roof of the property.
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