HIERARCHICAL STATIC SHADOW DETECTION METHOD

Patent №

US 7,366,323

Granted

2008-04-29

Filed 2004

Owner

RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YORK, THE

+1 more

Lab

AI components

2

ml · vision

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

10782230

There is provided a hierarchical shadow detection system for color aerial images. The system performs well with highly complex images as well as images having different brightness and illumination conditions. The system consists of two hierarchical levels of processing. The first level involves, pixel level classification, through modeling the image as a reliable lattice and then maximizing the lattice reliability using the EM algorithm. Next, region level verification, through further exploiting the domain knowledge is performed. Further analysis show that the MRF model based segmentation is a special case of the pixel level classification model. A quantitative comparison of the system and a state-of-the-art shadow detection algorithm clearly indicates that the new system is highly effective in detecting shadow regions in an image under different illumination and brightness conditions.

AI classification

Vision1.00
Machine learning1.00
Knowledge representation0.10
AI hardware0.06
Evolutionary computation0.02
Natural language0.01
Planning0.01
Speech0.00

Ownership

RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YORK, THE

assignment · 150100181

IP3 2019, SERIES 400 OF ALLIED SECURITY TRUST I

assignment · 514450248

Assignors

YAO, JIAN, ZHANG, ZHONGFEI (MARK)

On an employer assignment, the assignors are typically the inventors.

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