A dataset for evaluating multiple ellipse fitting methods of densely connected contours

Published: 3 December 2019| Version 2 | DOI: 10.17632/gnghdg9bzr.2
Contributor:
Hui Li

Description

Version 2: The Mathematica source codes "MultiEllipseFittingCodes.zip" are added in this version. Version 1: The dataset is made up of an experimental image and a set of synthetic images. The experimental image is an infrared handprint image (Hand1Raw.png). The synthetic images include one contour image containing 12 ellipses (12Raw.bmp), one contour image containing 20 ellipses (20Raw.bmp), eight contour images containing 4 ellipses each (4ARaw.bmp, 4BRaw.bmp, ... ,4HRaw.bmp), and a projected Ford circle image (FordDiskFitted.png). The file "Hand2MedianFiltered.png" is the median-filtered version of "Hand1Raw.png". And it can be further transformed to a contour image file "Hand3Thresholded.png" by thresholding. The x-y coordinates of the contours can be saved as csv files. The files "4A.csv" - "4H.csv" correspond to "4ARaw.bmp, 4BRaw.bmp, ... ,4HRaw.bmp". "12.csv" and "20.csv" correspond to "12Raw.bmp" and "20Raw.bmp" respectively. "FordDisk.csv" corresponds to "FordDiskFitted.png". "Hand01.csv" - "Hand07.csv" correspond to the seven parts of contour in file "Hand3Thresholded.png". Our goal is evaluating the multiply ellipse fitting framework. Multiple ellipses extracted from these contours can be saved as files like "...Fitted.png". Specifically, "4AFitted.png" - "4HFitted.png" correspond to "4ARaw.bmp, 4BRaw.bmp, ... ,4HRaw.bmp". "12Fitted.png" and "20Fitted.png" correspond to "12Raw.bmp" and "20Raw.bmp" respectively. "FordDiskFitted.png" corresponds to "FordDiskFitted.png". "HandFitted.png" corresponds to "Hand3Thresholded.png". Finally, all above-mentioned files have been compressed into three zip files separately. The "RawPictures.zip" contains all raw image files. The "ContourData.zip" contains all csv files. The "RawPictures.zip" contains all fitted ellipse files.

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Institutions

Beijing University of Chemical Technology

Categories

Image Processing, Pattern Recognition, Fitting Curve

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