A Salient Object Detection Technique Based on Color Divergence

Sana Sahar Guia, A. Laouid, R. Euler, Mohammed Amine Yagoub, A. Bounceur, Mohammad Hammoudeh
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Abstract

Nowadays, multimedia and visual computing advances in digital technology make a potential change in human life. Many applications exploit the captured images from autonomous entities as data sources for several goals. In fact, these captured images need to be interpreted in order to extract their external environment. The researchers of this domain will meet some challenges such as how to detect and interpret the images’ context. This paper is to propose an efficient technique that detects objects of a given image based on the color divergence. The results clearly show the accuracy and the computation speed of the proposed technique compared with other methods.
基于颜色发散的显著目标检测技术
如今,数字技术中的多媒体和视觉计算的进步使人类生活发生了潜在的变化。许多应用程序利用从自治实体捕获的图像作为多个目标的数据源。实际上,为了提取其外部环境,需要对这些捕获的图像进行解释。该领域的研究人员将面临一些挑战,如如何检测和解释图像的上下文。本文提出了一种基于颜色发散的图像目标检测方法。结果表明,与其他方法相比,该方法具有较高的计算精度和计算速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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