Image Classifier based on Histogram Matching and Outlier Detection using Hellinger distance

Anamika Gupta, Sarabjeet Kaur Kochchar, Anurag Joshi
Pages 407-413
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DOI https://doi.org/10.47738/jads.v4i4.114

Abstract


In this paper, we developed a prediction model based on histogram matching of Chest X-ray images. Hellinger distance metric is used to match two histograms. The chest x-ray images are pre-processed and converted to histograms. A benchmark histogram is obtained by finding the average of all pixel intensity values. Then outlier images are detected by comparing the histogram of an image with the benchmark histogram using the hellinger metric. Finally, a prediction method is proposed which matches the histogram of unseen images to histograms of nearest neighbor images.  Hypertuning of input parameters to the proposed prediction method is performed to get the best set of parameters. The proposed model gives an accuracy of 92.3 % and F1 score of 94.6 % on the training set, accuracy of 86.2% and F1 score of 89.6% on the test set.


Keywords


Histogram matching; Image classification; Hellienger distance; lazy classification; Outlier detection

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References


Chest X-Ray Images (Pneumonia) — https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia

Noronha, L., Tavares, J. M., & Cardoso, J. S. (2019). A KNN-Based Approach for Automatic Detection of Pneumonia in Pediatric Chest Radiographs. In Proceedings of the International Joint Conference on Neural Networks (IJCNN) (pp. 1-8).

Mahajan, A., Agrawal, A., & Phadke, G. K. (2020). Chest X-Ray Classification Using Local Binary Patterns and K-Nearest Neighbor Algorithm. In Proceedings of the IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT) (pp. 1-5).

Kaur, A., & Singh, R. (2021). Chest X-ray Image Classification Using K-Nearest Neighbor. In Proceedings of the IEEE International Conference on Computing, Communication and Automation (ICCCA) (pp. 1-5).

Doshi, S., & Kulkarni, P. (2021). Classification of Chest Radiographs for COVID-19 Detection Using K-Nearest Neighbor Algorithm. In Proceedings of the International Conference on Data Engineering and Communication Technology (ICDECT) (pp. 1-5).

Wang, J., & Wang, J. (2009). A novel KNN-based histogram matching method for content-based image retrieval. In Proceedings of the International Conference on Computational Intelligence and Security (pp. 672-676).

Shinde, S., & Patil, R. (2014). Image retrieval using color histogram and KNN classification technique. International Journal of Science, Engineering and Technology Research, 3(2), 339-342.

Zhang, W., Hu, Z., & Zhang, Z. (2015). Face recognition using histogram matching and KNN classification. In 2015 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC) (pp. 76-79).

Liu, Y., Wang, Z., & Gu, Y. (2018). Image classification based on a new KNN algorithm using histogram matching. In Proceedings of the International Conference on Management Science and Engineering (pp. 92-97).

Shah, K., Shah, R., & Shah, N. (2020). A novel KNN classification algorithm for image retrieval using histogram matching. In 2020 International Conference on Inventive Research in Computing Applications (pp. 1-6).

Lian, X., Chen, D., & Zhang, H. (2011). Image classification using Local Gabor Binary Pattern histogram sequence. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 1-8). This paper presents an image classification method that combines Gabor filters and local binary patterns with histogram representations.

Chen, C., Wang, Y., & Wu, Q. (2017). A histogram matching method based on Hellinger distance for image matching. In Proceedings of the 2017 3rd International Conference on Multimedia and Image Processing (ICMIP) (pp. 112-115).

Wang, Y., Zhang, D., & Liang, P. (2012). Gabor-based region covariance matrices for face recognition. Pattern Recognition Letters, 33(6), 708-717.

Kim, D., Kim, J., & Kim, J. (2011). Content-based image retrieval using local binary patterns and Hellinger distance. In Proceedings of the 13th International Conference on Advanced Communication Technology (ICACT) (pp. 1569-1573).

De La Torre, F., & Black, M. J. (2001). Robust principal component analysis for computer vision. In Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) (Vol. 1, pp. 362-369)..




DOI: https://doi.org/10.47738/jads.v4i4.114

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Journal of Applied Data Sciences

ISSN:2723-6471 (Online)
Publisher:Bright Publisher
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