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A Novel Saliency Measure Using Entropy and Rule of Thirds

  • Priyanka Bhatt
  • Navjot Singh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 748)

Abstract

Human intelligence can easily identify the visually attractive object, i.e., salient object with high accuracy in real time. It is an issue of concern to design an efficient computational model which can imitate human behavior such that the model attains better detection accuracy and takes less computation time. Until now, many models have been designed which are either better regarding detection accuracy or computation time but not both. This paper aims to realize a model that takes less computational time and at the same time attains higher detection accuracy. In this work, we propose a novel saliency detection model via the efficient use of entropy and boost the performance of saliency detection by employing the concept of the rule of thirds. The paper compares the performance of the proposed model with eighteen existing models on six publicly available datasets. With regard to precision, recall, and F-measure on all the six datasets, experimental results indicate better performance of the proposed model. Less computation time required by the proposed model in comparison to many state-of-the-art models.

Keywords

Salient object detection Entropy Rule of thirds Saliency map 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringNIT UttarakhandSrinagar (Garhwal)India

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