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An automatical algorithm based on local image properties

机译:一种基于局部图像属性的自动算法

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摘要

This study introduces the definition of local image properties. Using so-called local rules one can describe recognitions of interesting foreground object characteristics in images. We propose a novel algorithm to automatically detect interesting object characteristics in the images with local image properties, including the detections of edges or corners of objects in images. As applications, firstly, we compare the detection results of edges for objects in four images by our algorithm with the Roberts operator, Sobel operator, Prewitt operator, Log operator, Canny operator and cellular-neural-network-based algorithm (CNNBA). Secondly, we compare the detection results of corners for objects in three images by our algorithm with Harris operator, Shi-Tomasi operator and CNNBA. The experimental results have demonstrated that the proposed algorithm is able to detect correctly the all edges or corners of the objects in corresponding images, and has superior performance when compared with the other methods.
机译:本研究介绍了局部图像属性的定义。使用所谓的局部规则,可以描述图像中有趣的前景对象特征的识别。我们提出了一种新颖的算法来自动检测具有局部图像属性的图像中有趣的对象特征,包括检测图像中对象的边缘或角落。作为应用,首先,我们将我们的算法与Roberts运算符,Sobel运算符,Prewitt运算符,Log运算符,Canny运算符和基于蜂窝神经网络的算法(CNNBA)进行比较,比较四张图像中对象边缘的检测结果。其次,利用Harris算子,Shi-Tomasi算子和CNNBA算术,对算法在三幅图像中角点的检测结果进行了比较。实验结果表明,该算法能够正确地检测出相应图像中物体的所有边缘或角,与其他方法相比具有优越的性能。

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