Recognition of the Stomach Cancer Images with Probabilistic HOG Feature Vector Histograms by using HOG Features


KORKMAZ S. A. , Akcicek A., Binol H., KORKMAZ M. F.

15th IEEE International Symposium on Intelligent Systems and Informatics (SISY), Subotica, Serbia And Montenegro, 14 - 16 September 2017, pp.339-342 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Subotica
  • Country: Serbia And Montenegro
  • Page Numbers: pp.339-342

Abstract

In this study, normal (n), benign (b), and malign (m) stomach image cells have taken from faculty of Medicine the Firat University with Light Microscope help. Total number of stomach images are 180 which be 60 n, 60 b, and 60 m. 90 of these 180 stomach images have been used for testing purposes and 90 have been used for training purposes. The histograms of oriented gradient (HOG) feature extraction method were used for these images. HOG feature vectors were obtained by plotting HOG features on normal, benign, and malign original stomach images. Using these HOG property vectors, histograms of normal, benign, and malignant stomach images were plotted. Bins and h histogram values were obtained from these drawn histograms. A bandwidth range that can be distinguished between normal, benign, and malignant stomach images was calculated by comparing the bins and h values obtained for normal (n), benign (b) and malign (m) images. This bandwidth range was found to be 0.09-0.22. According to this bandwidth range, the accuracy result of stomach cancer images is found as 100%. When the h values of the HOG feature vector between these bandwidths are examined, the h values of normal and benign stomach images are found to be higher than those of a malignant stomach image. Between this bandwidth, the h value of the normal stomach image was found to be higher than the benign stomach image.