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[Software Engineering] fd DL : 0: 一种同时完成字符图像线段提取和细化的算法。在定义字符图像的线段区域、交点区域和子段区域,同时指出待细化字符图像是线段区域的集合的基础上,首先基于图像行(列)连通像素段来提取字符图像中所有的交点区域和子段区域,然后对属于同一线段区域的所有子段区域和交点区域进行合并,最后用Bernstein-Bezier多项式方法拟合每个线段区域的骨架 -At the same time, the image of a complete line of characters to extract and refine the algorithm. Characters in the definition of the segment image regions, regional and sub-paragraph intersection region to be refined at the same time pointed out that the character image is a collection of regional segment basis, first of all, image-based firms (column) connected pixels above the image to extract the characters of the intersection point of all regional and sub- Regional paragraph, and then belong to the same segment of the region above all regions and sub-regional merger point of intersection, the last used method of Bernstein-Bezier polynomial fitting region for each segment of the skeleton
Date : 2025-12-23 Size : 624kb User : 乐睿
[Software Engineering] Multisegmentationproject DL : 0: Segment Input image to different pardts
Date : 2025-12-23 Size : 1kb User : Edvard
[Software Engineering] improvedHough DL : 0: 首先检测图像中相邻的像素点并进行聚类, 形成一些相连的像素点的集合, 然后将聚类后的像素点进行感知编组, 细分成比原聚类线段更接近直线的线段, 最后对每段近似直线用随机 Hough变换进行检测-First detection in adjacent pixels of the image and clustering, form some connected set of pixels, then clustering Pixels after perception marshalling, subdivided into more than the original clustering line close to the straight line segment, at the end of each period of approximate straight line detection using randomized Hough transform
Date : 2025-12-23 Size : 255kb User : huangtingting
[Software Engineering] imageMorphology DL : 0: Thresholding is used to segment an image by setting all pixels whose intensity values are above a threshold to a foreground value and all the remaining pixels to a background value. Whereas the conventional thresholding operator uses a global threshold for all pixels, adaptive thresholding changes the threshold dynamically over the image. This more sophisticated version of thresholding can accommodate changing lighting conditions in the image, e.g. those occurring as a result of a strong illumination gradient or shadows.
Date : 2025-12-23 Size : 463kb User : dimpee
[Software Engineering] CE_Upload DL : 0: Thresholding is used to segment an image by setting all pixels whose intensity values are above a threshold to a foreground value and all the remaining pixels to a background value. Whereas the conventional thresholding operator uses a global threshold for all pixels, adaptive thresholding changes the threshold dynamically over the image. This more sophisticated version of thresholding can accommodate changing lighting conditions in the image, e.g. those occurring as a result of a strong illumination gradient or shadows.
Date : 2025-12-23 Size : 786kb User : dimpee
[Software Engineering] Shaped_Histograms DL : 0: Thresholding is used to segment an image by setting all pixels whose intensity values are above a threshold to a foreground value and all the remaining pixels to a background value. Whereas the conventional thresholding operator uses a global threshold for all pixels, adaptive thresholding changes the threshold dynamically over the image. This more sophisticated version of thresholding can accommodate changing lighting conditions in the image, e.g. those occurring as a result of a strong illumination gradient or shadows.-Thresholding is used to segment an image by setting all pixels whose intensity values are above a threshold to a foreground value and all the remaining pixels to a background value. Whereas the conventional thresholding operator uses a global threshold for all pixels, adaptive thresholding changes the threshold dynamically over the image. This more sophisticated version of thresholding can accommodate changing lighting conditions in the image, e.g. those occurring as a result of a strong illumination gradient or shadows.ff
Date : 2025-12-23 Size : 1.65mb User : dimpee
[Software Engineering] Thinking-in-Patterns DL : 0: Fractal geometry, together with the broader fields of nonlinear dynamics and complexity, represented a large segment of modern science at the end of the 20th century. Penetration of the resulting new paradigms into practically all academic disciplines has confirmed the fundamental assertion of universal formalism common to a wide range of human endeavors. This book contains an extended article by B B Mandelbrot, reviewing his contribution to fractal geometry and outlining some unsolved problems, with illustrations especially of finance and physics. It covers a range of multidisciplinary topics - the biology of aging, through the self-similar shape of plants, image decompression and solar magnetic fields, to sound reflection in the street. The book is a treasure trove for innovative researchers working in fields related to fractal geometry.-Fractal geometry, together with the broader fields of nonlinear dynamics and complexity, represented a large segment of modern science at the end of the 20th century. Penetration of the resulting new paradigms into practically all academic disciplines has confirmed the fundamental assertion of universal formalism common to a wide range of human endeavors. This book contains an extended article by B B Mandelbrot, reviewing his contribution to fractal geometry and outlining some unsolved problems, with illustrations especially of finance and physics. It covers a range of multidisciplinary topics- the biology of aging, through the self-similar shape of plants, image decompression and solar magnetic fields, to sound reflection in the street. The book is a treasure trove for innovative researchers working in fields related to fractal geometry.
Date : 2025-12-23 Size : 1.06mb User : 张小寒
[Software Engineering] matlab-car DL : 0: 车辆自动识别(AVI)是智能交通系统中的一项重要技术。汽车牌照识别是实现车辆自动识别的一种重要的技术手段。而从包含汽车牌照的图像中准确、快速地分割出牌照区域是实现车牌自动识别的一个关键步骤。本文主要研究了汽车牌照识别中车牌定位问题。车牌定位分为两步进行，首先对车牌进行初定位，对初定位后的车牌图像进行二值化、几何矫正，然后再精确定位车牌区域。同时，在matlab环境下仿真了汽车牌照识别，仿真结果表明，本文算法能很好的识别汽车牌照。 -the Vehicle automatic identification (AVI) is the intelligent transportation system is an important technology. Car licence plate recognition is to realize the automatic recognition of vehicle is a kind of important technical means. And the car licence contains accurately and rapidly in image segment the licence area is realizing automatic license plate recognition is a key step. This paper mainly studies the car license plate location in the licence plate recognition. License plate localization is divided into two steps of vehicle license plate, first to early, early after positioning the license plate location binary image, geometric correction, then accurate positioning license plate area. Meanwhile, in matlab simulation the car licence plate recognition, the simulation results show that the algorithm can very good recognition car licence.
Date : 2025-12-23 Size : 1.49mb User : wfyan