Row Crop's Identication Through Hough Transform using Images Segmented by Robust Fuzzy Possibilistic C-Means

Abstract

The Hough transform (HT) is a widely used method for line detection and recognition, due to its robustness. But its performance is strongly dependent on the applied segmentation technique. On the other hand, Fuzzy C-Means (FCM) has been widely used in image segmentation because it has a good performance in a large class of images. However, it is not good for noisy images, so that to overcome this weakness several modications to FCM have been proposed, like Robust Fuzzy Possibilistic C-Means (RFPCM). In this paper, we propose to use the RFPCM algorithm for the segmentation of crops images in order to apply the HT to detect lines in row crops for navigation purposes. The proposed method gives better results compared with techniques based on visible spectral-index or Specic threshold-based approaches.