G.G.Naidu; Y.Srinivas

Model Based Approach for Identification of Relevant Images from Ancient Paintings

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Author(s)

G.G.Naidu ^1,* Y.Srinivas ²

1. Dept of Computer Engg, Govt Polytechnic, Anakapalli, Visakhapatnam - 531001, India

2. Dept of IT, GITAM University, Visakhapatnam -530045, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijem.2017.05.04

Received: 12 Jan. 2016 / Revised: 11 Jan. 2017 / Accepted: 28 Mar. 2017 / Published: 8 Sep. 2017

Index Terms

GBLMM, classification, painting, retrieval, stroke

Abstract

In this paper an attempt is made to retrieve the relevant paintings based on the approach of the artist using Generalized Bivariate Laplacian Mixture Model (GBLMM). This article helps in understanding the outline of assorted artists and help as a means to categorize a scrupulous painting based on the style or the text ingrained within the images. To profile the artist style GBLMM is used. The projected model helps to discriminate the strokes of the artists and lend a hand in the classification of paintings. The proposed model is implemented using high resolution Chinese painting images.

Cite This Paper

G.G.Naidu, Y.Srinivas,"Model Based Approach for Identification of Relevant Images from Ancient Paintings", International Journal of Engineering and Manufacturing(IJEM), Vol.7, No.5, pp.39-47, 2017. DOI: 10.5815/ijem.2017.05.04

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