A novel region-growing algorithm for the segmentation of endoscopic images is proposed in this paper. The objective of the research work is fast and accurate segmentation of gastrointestinal lumen from the endoscopic images for real-time applications. The proposed technique consists of a dual-step methodology in which a quasi Region of Interest (qROI) is segmented first using a global thresholding technique and then the actual lumen is extracted using differential region growing. An adaptive progressive thresholding technique is used to obtain qROI for a given endoscopic image. The centre of mass of qROI acts as the seed for the region growing in the next step. A differential region growing technique is suggested which grows the region on the basis of a similarity criterion. A dynamic hill-clustering method is utilised to ensure the effectiveness of the terminating condition during the growth process. The proposed scheme is faster than the conventional gradient based region-growing technique. The accuracy and high speed response of the proposed technique is validated with several endoscopic images and the results are presented.