“IMAGE CLASSIFICATION USING DATA

MINING TECHNIQUES”

PRESENTED BY :

Er. SANTOSH KUMAR DASH | MTECH CSE, Utkal UniversityASE| Tata Consultancy Services Limited

INTERNATIONAL CONFERENCEOn

“Innovative Research in Computer Science, E-Learning, Information & Communication Technology”

(CSIT– 2016)

Contents Introduction Motivation Objective Proposed Methodology Experimental Results Conclusion and Future Work

Introduction Experiments are performed on three different images

such as: medical image, satellite image and scenery image.

Medical Image Satellite Image Scenery Image

Objective Feature extraction from various images.

Region of Interest calculation.

Application of Data Mining Techniques for classification.

Proposed Methodology

Proposed Methodology

Normal Image Noisy Image Filtered Image

Proposed Methodology

Normal Image Noisy Image Filtered Image

Proposed Methodology

Normal Image Noisy Image Filtered Image

Proposed Methodology Classifiers used

Decision Tree(J48)

Naïve Bayes

Random Forest

Experimental Results For cancer image- Random Forest algorithm gives better

accuracy.

For scenery image-J48 gives better accuracy

For satellite image- Random forest is better for normal image and Naïve Bayes is better for noisy image.

Conclusion and future work Decision tree, Naïve Byes and random forest data mining

techniques are applied to classify the region of interest.

Filtered image enhances the classification accuracy

Filtering options with large scale images are to be considered in future.

Thank YouAny Questions?