Abstract:
Wireless capsule endoscopy has now been used in medicine to take pictures of the
gastrointestinal tract. The wireless capsule camera takes many pictures, which makes it
difficult to analyze with the naked eye. Therefore, in this paper, three methods of automatic
classification of bleeding areas were proposed: K-Mean Clustering, consisting of before color
Thresholder and after Color Thresholder, KNN, and Clustering methods. RGB color values were
used to classify the bleeding area, and a confusion matrix was used to test the efficiency. The
results of the system consisted of the before color Thresholder, after Color Thresholder, KNN,
and grouping data by RGB color values, It was found that the loU was used to measure the
performance , each of which scored 51.18%, 59.64%, 43.06%, and 61.88%, respectively. When
changing the image dataset, the results of the system consisted of the before color
Thresholder, after Color Thresholder, and grouping data method by RGB color values as
follows, loU scored 15.77%, 19.77%, and 46.22%, respectively. Based on the performance
experiments conducted on the two data groups, it was demonstrated that the RGB color data
grouping method was the most efficient. As it pertains to a specific classification of blood
regions, this method's RGB values encompass a more comprehensive range of color values
than other methods.
