Abstract: Automatic determination of blood in less bright or
noisy capsule endoscopic images is difficult due to low S/N ratio.
Especially it may not be accurate to analyze these images due to the
influence of external disturbance. Therefore, we proposed detection
methods that are not dependent only on color bands. In locating
bleeding regions, the identification of object outlines in the frame and
features of their local colors were taken into consideration. The results
showed that the capability of detecting bleeding was much improved.
Abstract: The colors of the human skin represent a special
category of colors, because they are distinctive from the colors of
other natural objects. This category is found as a cluster in color
spaces, and the skin color variations between people are mostly due
to differences in the intensity. Besides, the face detection based on
skin color detection is a faster method as compared to other
techniques. In this work, we present a system to track faces by
carrying out skin color detection in four different color spaces: HSI,
YCbCr, YES and RGB. Once some skin color regions have been
detected for each color space, we label each and get some
characteristics such as size and position. We are supposing that a face
is located in one the detected regions. Next, we compare and employ
a polling strategy between labeled regions to determine the final
region where the face effectively has been detected and located.