Adaptive threshold for background subtraction in moving object detection using Fuzzy C-Means clustering

Background subtraction is the important part of moving object detection. The problem of background subtraction is threshold selection strategy. This paper proposed a Fuzzy C-Means (FCM) algorithm to produce an adaptive threshold for background subtraction in moving object detection. To evaluate the performance, FCM were compared against standard Otsu algorithm as threshold selection strategy. Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR) was used to measure the performance. Based on the experiment, the MSE of FCM is lower than MSE of Otsu and PSNR of FCM is higher than PSNR of Otsu. The result proved that FCM is promising to classify the pixels as foreground or background in moving object detection.