Image Recognition Using Machine Learning with the Aid of MLR

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Meherunnesa Tania 1,* Diba Afroze 1 Jesmin Akhter 2 Abu Sayed Md. Mostafizur Rahaman 1 Md. Imdadul Islam 1

1. Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh

2. Institute of Information Technology, Jahangirnagar University, Dhaka, Bangladesh

* Corresponding author.


Received: 10 Aug. 2021 / Revised: 2 Sep. 2021 / Accepted: 22 Sep. 2021 / Published: 8 Dec. 2021

Index Terms

Logistic regression, Eigen decomposition, objective function, scatterplot and entropy based combined algorithm


In this paper, we use three machine learning techniques: Linear Discriminant Analysis (LDA) along different Eigen vectors of an image, Fuzzy Inference System (FIS) and Fuzzy c-mean clustering (FCM) to recognize objects and human face. Again, Fuzzy c-mean clustering is combined with multiple linear regression (MLR) to reduce the four-dimensional variable into two dimensional variables to get the influence of all variables on the scatterplot. To keep the outlier within narrow range, the MLR is again applied in logistic regression. Individual method is found suitable for particular type of object recognition but does not reveal standard range of recognition for all types of objects. For example, LDA along Eigen vector provides high accuracy of detection for human face recognition but very poor performance is found against discrete objects like chair, butterfly etc. The FCM and FIS are found to provide moderate result in all kinds of object detection but combination of three methods of the paper provide expected result with low process time compared to deep leaning neural network.  

Cite This Paper

Meherunnesa Tania, Diba Afroze, Jesmin Akhter, Abu Sayed Md. Mostafizur Rahaman, Md. Imdadul Islam, " Image Recognition Using Machine Learning with the Aid of MLR", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.13, No.6, pp. 12-22, 2021. DOI: 10.5815/ijigsp.2021.06.02


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