• Heena Noor
• sucheta Sharma

In this paper, effective approach for early detection of abdominal disease using segmentation and classification is proposed. Abdominal images contains distortion in terms of noise initially, hence filtering is required in order to remove noise from the image. Segmentation is the next step used to extract lesion area. Results of segmentation are compared against various well known measures and result obtained is commendable. Support vector machine and fuzzy neural technique is used for classification. Results show significant improvement over SVM+KNN. Accuracy is improved by 45%, and error rate is decreased by 30%.

Inflammatory Bowel disease, Pre-processing, Segmentation, SVM, KNN

"Hybrid Approach Of SVM and KNN to detect abdominal diseases with high classification accuracy", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.186-195, March-2019, Available :http://www.jetir.org/papers/JETIR1903327.pdf

"Hybrid Approach Of SVM and KNN to detect abdominal diseases with high classification accuracy", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp186-195, March-2019, Available at : http://www.jetir.org/papers/JETIR1903327.pdf