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Identifying the presence of bacteria on digital images by using asymmetric distribution with k-means clustering algorithm

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Abstract

This paper is mainly aimed at the decomposition of image quality assessment study by using Three Parameter Logistic Mixture Model and k-means clustering (TPLMM-k). This method is mainly used for the analysis of various images which were related to several real time applications and for medical disease detection and diagnosis with the help of the digital images which were generated by digital microscopic camera. Several algorithms and distribution models had been developed and proposed for the segmentation of the images. Among several methods developed and proposed, the Gaussian Mixture Model (GMM) was one of the highly used models. One can say that almost the GMM was playing the key role in most of the image segmentation research works so far noticed in the literature. The main drawback with the distribution model was that this GMM model will be best fitted with a kind of data in the dataset. To overcome this problem, the TPLMM-k algorithm is proposed. The image decomposition process used in the proposed algorithm had been analyzed and its performance was analyzed with the help of various performance metrics like the Variance of Information (VOI), Global Consistency Error (GCE) and Probabilistic Rand Index (PRI). According to the results, it is shown that the proposed algorithm achieves the better performance when compared with the previous results of the previous techniques. In addition, the decomposition of the images had been improved in the proposed algorithm.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, RAGHU Engineering College (A), Visakhapatnam, AP, India

    K. V. Satyanarayana

  2. Department of Computer Science and Engineering, Vignan’s Institute of Information Technology (A), Visakhapatnam, 530049, India

    N. Thirupathi Rao

  3. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Greenfield, Vaddeswaram, Guntur, 522502, India

    Debnath Bhattacharyya

  4. Department of Computer Science and Information Management, Providence University, 200, Sec. 7, Taiwan Boulevard, Shalu Dist, Taichung City, 43301, Taiwan, Republic of China

    Yu-Chen Hu

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  1. K. V. Satyanarayana
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  2. N. Thirupathi Rao
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  3. Debnath Bhattacharyya
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  4. Yu-Chen Hu
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Correspondence to Yu-Chen Hu.

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Satyanarayana, K.V., Rao, N.T., Bhattacharyya, D. et al. Identifying the presence of bacteria on digital images by using asymmetric distribution with k-means clustering algorithm. Multidim Syst Sign Process 33, 301–326 (2022). https://doi.org/10.1007/s11045-021-00800-0

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  • DOI: https://doi.org/10.1007/s11045-021-00800-0

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