首页> 外文会议>Southern African Universities Power Engineering Conference;Conference on Robotics and Mechatronics;Conference on Pattern Recognition Association of South Africa >A front-end technique for visual gold detection and localization – Towards automation of the gold panning process.
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A front-end technique for visual gold detection and localization – Towards automation of the gold panning process.

机译:一种前端技术,可视金检测与本土化 - 朝向金淘汰的自动化。

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摘要

To do away with the time consuming, error prone and expert dependent gold detection and localization in the current gold panning procedure, automatic image-based techniques are considered in this paper. Identifying and locating gold particles during the gold panning process is a fundamental process in gold extraction. In the automation of the gold panning process and robotic handling it is important to identify and locate the gold particles in the images captured by the image sensor. Image segmentation is a vital step in image simplification, image understanding and object detection. Image segmentation is the process of identifying and extracting homogeneous regions (segments) in an image satisfying a homogeneity criterion based on features formulated from spectral components of the image. Three image thresholding techniques were tested and evaluated on sample gold panning images. Color image thresholding in the CIELAB color space performed better in detecting and locating gold particles in an image. The proposed method will serve as a front-end technique for an automated gold panning system as it will automate the visual feature identification of gold particles and aid in the control of the handling system of the gold particles during the panning process.
机译:要消耗耗时,易于易于和专家依赖金检测和本地化在当前的金淘汰程序中,本文考虑了自动图像的技术。在金淘汰过程中识别和定位金颗粒是金提取的基本过程。在黄金平移过程和机器人处理的自动化中,重要的是要识别并定位由图像传感器捕获的图像中的金颗粒。图像分割是图像简化,图像理解和对象检测的重要步骤。图像分段是基于由图像的光谱分量配制的特征来识别和提取满足同一性标准的图像中的均匀区域(段)的过程。测试和评估了三种图像阈值技术在样品金平移图像上进行了测试。 Cielab颜色空间中的彩色图像阈值化更好地检测和定位图像中的金颗粒。该方法将用作自动金平移系统的前端技术,因为它将自动化金颗粒的视觉特征识别,并帮助控制淘汰过程中金颗粒的处理系统。

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