A comparative analysis of techniques for extracting features from the object in image processing

Touka Hafsia, H. Tlijani, K. Nouri
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引用次数: 1

Abstract

Visual informations is very rich to control and pursue mobile robots, like wheeled mobile robots, underwater robots and aerospace mobile robots, etc. These are considered as mobile robots that move in different spaces, their main problem in this case is navigation especially in unknown environments. In effect, this navigation is possible only by the localisation and orientation of the robot by using different embedded sensors. We have the camera which is a necessary sensor in this work, it is an embedded instrument that gives very rich visual information as a sensor complementing the other sensors. In this context, the recognition of objects from visual informations is a main function among the functions very useful in image processing tasks due to its varied applications in the field of robotics. Based on the analysis of this informations and the determination of image features like color or shape or object primitives (points, lines, edges, etc.) or some other features. What interest us in this paper, various feature extraction techniques and classification of point and edge detection are discussed which are required for object recognition showing advantages and disadvantages of the selected algorithms. So, points and edge detection refers to the process of identifying and detecting sharp discontinuities in an image. In this work, we try to develop a novel algorithm using the work on the existing to create a novel detector.
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图像处理中物体特征提取技术的比较分析
对于轮式移动机器人、水下移动机器人和航空航天移动机器人等移动机器人的控制和跟踪来说,视觉信息是非常丰富的。这些被认为是在不同空间移动的移动机器人,它们在这种情况下的主要问题是导航,特别是在未知环境中。实际上,这种导航只能通过使用不同的嵌入式传感器来定位和定位机器人。我们有相机,这是一个必要的传感器在这项工作中,它是一个嵌入式仪器,提供非常丰富的视觉信息,作为一个传感器补充其他传感器。在这种情况下,从视觉信息中识别物体是图像处理任务中非常有用的功能之一,因为它在机器人领域的应用非常广泛。基于对这些信息的分析和图像特征的确定,如颜色或形状或物体原语(点、线、边等)或其他一些特征。本文讨论了目标识别所需的各种特征提取技术和点边缘检测分类,并展示了所选算法的优缺点。因此,点边缘检测是指对图像中明显的不连续点进行识别和检测的过程。在这项工作中,我们试图开发一种新的算法,利用现有的工作来创建一个新的检测器。
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