A Method for Detecting Breaches and New Objects in Multiple Outdoor Images

This paper presents a new automated change detection method for detecting breaches in the integrity ofand attached objects in front of fence wires in multiple outdoor images of the same scene containing fence wiresacquired by a mobile camera from slightly different viewing positions, angles and at different times. To detectsignificant changes, edges of fence wires firstly have to be extracted from multiple outdoor images using acombination of the Sobel detector and an adaptive thresholding technique. Secondly, morphological operationssuch as dilation and erosion are applied into binary images produced by the previous process in enhancing thebinary images. Next, an area-based algorithm is applied to enhanced binary images in separating small and bigobjects based on their average areas determined once in the calibration process. Finally, objects that survive arethen fed into a fuzzy inference system in calculating their possibility values. Based on these possibility values, thesurvived objects can be classified as significant or unimportant changes. Experimental results demonstrate thatthe method has a high success rate (94.12%) in detecting true positives in these kinds of multiple outdoor images