A new approach to the automatic extraction of the lumen region and its boun
dary for gastrointestinal (GI) endoscopic images is presented. First, a qua
si region of interest, the darker regions of the image, is segmented using
a region splitting scheme termed progressive thresholding. The centre of ma
ss of this segmented region acts as a seed for further processing. Then the
lumen region is obtained using a region growing technique called the integ
rated neighbourhood search (INS). A new quad structure based technique is i
ntroduced to enhance the INS speed significantly. A back projection algorit
hm is suggested to optimise the search for pixels belonging to the lumen re
gion and boundary. A boundary-thinning algorithm is also proposed to remove
the redundant pixels from the lumen boundary and to generate a connected s
ingle pixel width boundary. The proposed approach does not need a priori kn
owledge about the image characteristics. The experimental results indicate
that the proposed technique enhances the speed of conventional INS by 45.5%
to 28.6% based on the lumen size varying from 22 709 pixels to 4947 pixels
. The main advantage of the proposed technique is its high-speed response t
hat facilitates real-time analysis of endoscopic images.