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Automatic Change Detection Method for an Indoor Environment


Affiliations
1 Department of Computer Science, Jeppiaar Engineering College, Chennai-119, India
 

Detecting changed regions in multiple images of the same scene taken at different times is of great interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. The goal is to identify the set of pixels that are significantly different between the last image of the sequence and the previous images. This paper presents a study of an automatic change detection method for multiple images of the same scene acquired by a mobile-camera from different positions with no illumination changes. The proposed method used for this study consists of three steps:(1) automatic image registration, (2) temporal differencing and (3) unimportant changes removal. The results in this paper show that the presented method successfully detects new objects in the scene from the multiple images.

Keywords

Automatic Image Registration, Temporal Differencing, Unimportant Changes Removal.
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  • Automatic Change Detection Method for an Indoor Environment

Abstract Views: 125  |  PDF Views: 0

Authors

D. Beulah David
Department of Computer Science, Jeppiaar Engineering College, Chennai-119, India

Abstract


Detecting changed regions in multiple images of the same scene taken at different times is of great interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. The goal is to identify the set of pixels that are significantly different between the last image of the sequence and the previous images. This paper presents a study of an automatic change detection method for multiple images of the same scene acquired by a mobile-camera from different positions with no illumination changes. The proposed method used for this study consists of three steps:(1) automatic image registration, (2) temporal differencing and (3) unimportant changes removal. The results in this paper show that the presented method successfully detects new objects in the scene from the multiple images.

Keywords


Automatic Image Registration, Temporal Differencing, Unimportant Changes Removal.