Vision prehension with CBIR for cloud robo

Asif Khan, S. Deep, Jian-ping Li, K. Kumar, R. Shaikh, Faraz Hasan
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引用次数: 8

Abstract

Content Based Image Retrieval is very hottest research area in computer vision and image processing. To perceive arbitrary natural scene from complex environment is a challenging issue in visual imaging and processing research area. Neural Network is a grid of “neuron like” nodes, in this paper we follow towards Neural Network (NN), is committed to contributing a new technical concept for the scene understanding and recognition by consolidating new intellectual visual features into the scene expression, which can be very crucial and provide cognitive intelligence to cloud robot. Inspired by Artificial Neural Network intelligence due to its dynamic nature, we make use of the attributes of the Gabor filter and Laplacian of Gaussian filter which is to be akin to robot visual perception, and apply the wavelet transform to inspect a new approach in complex environment natural scene perception and understanding for virtual phenomena. Through the study of Neural Network, the perception ability of the natural scene image from complex environment for cloud robot is enhanced with the integration of cognitive visual features and the scene expression.
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基于CBIR的云机器人视觉抓取
基于内容的图像检索是计算机视觉和图像处理领域的研究热点。从复杂环境中感知任意自然场景是视觉成像与处理研究领域的一个具有挑战性的问题。神经网络是一个由“神经元”节点组成的网格,本文将神经网络(NN)作为研究方向,致力于通过将新的智能视觉特征整合到场景表达中,为场景理解和识别提供一个新的技术概念,这对云机器人的认知智能至关重要。受人工神经网络智能动态特性的启发,利用Gabor滤波器和高斯滤波器中类似机器人视觉感知的拉普拉斯算子的特性,将小波变换应用于复杂环境中对自然场景的感知和虚拟现象的理解,是一种新的方法。通过对神经网络的研究,将认知视觉特征与场景表达相结合,增强云机器人对复杂环境中自然场景图像的感知能力。
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