  Cervical Cancer is one of the most common forms of cancer in women worldwide.
Most cases of cervical cancer can be prevented through screening programs aimed
at detecting precancerous lesions. During Digital Colposcopy, Specular
Reflections (SR) appear as bright spots heavily saturated with white light.
These occur due to the presence of moisture on the uneven cervix surface, which
act like mirrors reflecting light from the illumination source. Apart from
camouflaging the actual features, the SR also affects subsequent segmentation
routines and hence must be removed. Our novel technique eliminates the SR and
makes the colposcopic images (cervigram) ready for segmentation algorithms. The
cervix region occupies about half of the cervigram image. Other parts of the
image contain irrelevant information, such as equipment, frames, text and
non-cervix tissues. This irrelevant information can confuse automatic
identification of the tissues within the cervix. The first step is, therefore,
focusing on the cervical borders, so that we have a geometric boundary on the
relevant image area. We have proposed a type of modified kmeans clustering
algorithm to evaluate the region of interest.
