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Image decomposition by using the Hough transform with cubic B-spline curve.

机译:使用具有三次B样条曲线的Hough变换进行图像分解。

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摘要

In this dissertation, various algorithms based on the Hough transform with cubic B-spline curves (HTCB) are developed for a variety of image processing applications, such as line or edge detection, curve-enclosed object detection.; First, an algorithm is presented using the Hough transform method for image decomposition into and description by curves representing image elements. The curves used for this representation are the periodic cubic B-spline curves. The image curves so represented can then be efficiently stored, resulting in a concise description of the objects' shapes. Other computation advantages, important among which is a small quantization error, are shown to be associated with the new algorithm. The new approach takes advantage of the well-known properties of the uniform cubic B-spline curves that changes in the coordinates of any vertex will only affect three segments in the immediate vicinity of the changed vertex. The general idea underlying this algorithm is to fit a B-spline to the curve and find the control vertices from Hough space (parametric space). This process is followed by the de Boor algorithm and a subdivision algorithm which can be used to reconstruct the detected curve.; Two algorithms based on the image decomposition by the Hough transform with cubic B-spline curves (IDHTCB) are proposed for circle and ellipse object detection. We pre-process the noisy images by using edge detection schemes such as gradient detectors, homogeneous detectors, etc. After edge detection of the input image, we remove the noise and extract the corresponding straight lines (symmetric horizontal and vertical lines) of the object by using the IDHTCB algorithm. These symmetric horizontal and vertical lines will give us the location of the objects. The curve-enclosed object is then reconstructed by using the properties of the object or the inversion formula (de Boor algorithm or subdivision algorithm).; Finally, the restoration approaches based on the IDHTUCB Algorithm with median filter (IDHTUCBMF) is proposed for improving both spatial degradation and point degradation. It yields excellent results in restoring the image as compared to the median filter and the average filter.
机译:本文针对具有线性B样条曲线(HTCB)的霍夫变换,开发了多种算法,用于各种图像处理应用,例如线或边检测,曲线封闭目标检测。首先,提出了一种使用霍夫变换方法的算法,用于将图像分解为代表图像元素的曲线并由其描述。用于此表示的曲线是周期性三次B样条曲线。这样表示的图像曲线可以被有效地存储,从而对对象的形状进行了简洁的描述。其他计算优势,其中重要的是小的量化误差,也被证明与新算法相关。新方法利用了均匀三次B样条曲线的众所周知的特性,即任何顶点坐标的变化只会影响变化后的顶点附近的三个线段。该算法的基本思想是将B样条拟合到曲线上,并从霍夫空间(参数空间)中找到控制顶点。此过程之后是de Boor算法和细分算法,可用于重建检测到的曲线。提出了两种基于霍夫变换的三次B样条曲线图像分解算法(IDHTCB),用于圆和椭圆物体的检测。我们通过使用诸如梯度检测器,齐次检测器等边缘检测方案对噪声图像进行预处理。在对输入图像进行边缘检测之后,我们去除了噪声并提取了对象的相应直线(对称的水平和垂直线)通过使用IDHTCB算法。这些对称的水平和垂直线将为我们提供对象的位置。然后,通过使用对象的属性或反演公式(de Boor算法或细分算法)来重建曲线封闭的对象。最后,提出了一种基于带中值滤波器的IDHTUCB算法的恢复方法(IDHTUCBMF),以改善空间退化和点退化。与中值滤波器和平均滤波器相比,它在恢复图像方面产生了出色的结果。

著录项

  • 作者

    Wang, Ted Mao-Hsin.;

  • 作者单位

    Polytechnic University.;

  • 授予单位 Polytechnic University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 1996
  • 页码 164 p.
  • 总页数 164
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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