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Object Detection by 2-D Continuous Wavelet Transform

机译:二维连续小波变换的目标检测

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The use of two dimensional (2-D) continuous wavelet analysis has not been extensive for image processing using wavelets. It has been overshadowed by the 2-D discrete dyadic wavelet transform (DWT) due to its compactness and excellent performance in coding, data compression, image reconstruction, etc. However, the 2-D DWT has some restrictions on the scale and position parameters, and it does not detect all the features of an image unless properly tuned. The 2-D continuous wavelet transform (CWT), on the other hand, is more flexible and provides complete control over the scale and position parameters, and thus it is capable of extracting various features of an image, which cannot be accomplished by the DWT. It is shown that sharp edges can be extracted at lower scales of the 2-D CWT. In this paper, an algorithm is developed to detect focused objects in an image/video using the 2-D CWT. The first step in this algorithm is to extract the edges of focused objects using the 2-D CWT. The object detected is converted to binary image. Some applications of object detection method in image and video processing are mentioned.
机译:二维(2-D)连续小波分析的使用尚未广泛用于使用小波的图像处理。由于它的紧凑性和在编码,数据压缩,图像重建等方面的出色性能,它已被二维离散二进小波变换(DWT)所掩盖。但是,二维离散小波变换在比例尺和位置参数上有一些限制,除非进行适当调整,否则它不会检测图像的所有功能。另一方面,二维连续小波变换(CWT)更灵活,可以完全控制比例和位置参数,因此它能够提取图像的各种特征,而DWT无法完成。结果表明,可以在二维CWT的较小尺度上提取出锐利的边缘。在本文中,开发了一种算法来使用二维CWT检测图像/视频中的聚焦对象。该算法的第一步是使用2-D CWT提取聚焦对象的边缘。检测到的对象将转换为二进制图像。提出了对象检测方法在图像和视频处理中的一些应用。

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