Shadow detection in color aerial images based on HSI space and color attenuation relationship

Wenxuan Shi,Jie Li

doi:10.1186/1687-6180-2012-141

Abstract

Many problems in image processing and computer vision arise from shadows in a single color aerial image. This article presents a new algorithm by which shadows are extracted from a single color aerial image. Apart from using the ratio value of the hue over the intensity in some state-of-the-art algorithms, this article introduces another ratio map, which is obtained by applying the saturation over the intensity. Candidate shadow and nonshadow regions are separated by applying Otus’s thresholding method. The color attenuation relationship that describes the relationship between the attenuation of each color channel is derived from the Planck’s blackbody irradiance law. For each region, the color attenuation relationship and other determination conditions are performed iteratively to segment it into smaller sub-regions and to identify whether each sub-region is a true shadow region. Compared with previous methods, the proposed algorithm presents better shadow detection accuracy in the images that contain some dark green lawn, river, or low brightness shadow regions. The experimental results demonstrate the advantage of the proposed algorithm.

Highlights

Shadows in digital images are either helpful or troublesome in image processing and pattern recognition
Instead of using only one ratio map proposed in their articles, we propose a novel method for shadow detection in color aerial images, which uses two ratio maps plus color attenuation relationship derived from blackbody radiator model
Where the true positive (TP) denotes the number of true shadow pixels correctly identified; the false negative (FN) denotes the number of true shadow pixels identified as nonshadow pixels; the false positive (FP) denotes the number of nonshadow pixels identified as shadow

Summary

Introduction

Shadows in digital images are either helpful or troublesome in image processing and pattern recognition. Chung et al [1] proposed a successive thresholding scheme for detecting shadows in color aerial images. Instead of using only one ratio map proposed in their articles, we propose a novel method for shadow detection in color aerial images, which uses two ratio maps plus color attenuation relationship derived from blackbody radiator model. In order to enlarge the RM value gap between shadow and nonshadow pixels near a threshold Ts, the modified ratio map RM' is defined by 8

À GÞ2 þ ðR À BÞðG

Objective evaluation

Method

Findings

Conclusions