{"id":4189,"date":"2020-09-30T10:30:55","date_gmt":"2020-09-30T14:30:55","guid":{"rendered":"https:\/\/blogs.mathworks.com\/steve\/?p=4189"},"modified":"2020-09-30T10:30:55","modified_gmt":"2020-09-30T14:30:55","slug":"how-to-detect-an-x-rite-colorchecker-chart","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/steve\/2020\/09\/30\/how-to-detect-an-x-rite-colorchecker-chart\/","title":{"rendered":"How to Detect an X-Rite® ColorChecker® Chart"},"content":{"rendered":"

When I saw this picture, I was really tempted to take it into the local garden nursery and ask them how to keep color checker charts out of my rhododendrons.<\/p>

\"\" <\/p>

No, no, this post is not really about protecting gardens against unusual invaders. I was looking over the just-released R2020b Image Processing Toolbox, and I noticed that a number of color science related features made it into the release. Since I was posting about color a couple of months ago, I thought I would highlight some of these new features here. Today, I'll start with a function that can detect the location of an X-Rite® ColorChecker® chart into the workspace.<\/p>

First, let's read our test image. This file contains the image shown above.<\/p>

A = imread('colorCheckerTestImage-with-credit.jpg'<\/span>);\r\n<\/pre>
Next, create a colorChecker<\/tt> object from the image.<\/p>
chart = colorChecker(A)\r\n<\/pre>
\r\nchart = \r\n\r\n  colorChecker with properties:\r\n\r\n                 Image: [1024×1541×3 uint8]\r\n    RegistrationPoints: [4×2 double]\r\n             ColorROIs: [24×1 struct]\r\n\r\n<\/pre>
When created, the colorChecker<\/tt> object searches to find the position of the color checker chart in the image. The optional Downsample<\/tt> and Sensitivity<\/tt> parameters control some aspects of the automatic detection.<\/p>
The displayChart<\/tt> function shows the image and places markers and numbers to identify the detected chart corners (called \"registration points\") and numbered color squares.<\/p>
displayChart(chart)\r\n<\/pre>\"\" 
axis([725 1350 430 850])\r\n<\/pre>\"\" 
The measureColor<\/tt> function produces a table containing the measured values of the detected color chart squares, together with their reference values. It also includes $\\Delta_E$, a measure of perceptual color difference.<\/p>
T = measureColor(chart)\r\n<\/pre>
\r\nT =\r\n\r\n  24×9 table\r\n\r\n    ROI         Color          Measured_R    Measured_G    Measured_B    Reference_L    Reference_a    Reference_b    Delta_E\r\n    ___    ________________    __________    __________    __________    ___________    ___________    ___________    _______\r\n\r\n     1     {'DarkSkin'    }       160           128           119           37.54          14.37          14.92       19.817 \r\n     2     {'LightSkin'   }       229           200           191           64.66          19.27           17.5       22.587 \r\n     3     {'BlueSky'     }       146           191           241           49.32          -3.82         -22.54       27.312 \r\n     4     {'Foliage'     }       130           161           117           43.46         -12.74          22.72       20.404 \r\n     5     {'BlueFlower'  }       175           187           248           54.94           9.61         -24.79       23.073 \r\n     6     {'BluishGreen' }       155           232           226           70.48         -32.26          -0.37       18.284 \r\n     7     {'Orange'      }       255           161            99           62.73          35.83           56.5       16.114 \r\n     8     {'PurplishBlue'}       130           164           254           39.43          10.75         -45.17       28.889 \r\n     9     {'ModerateRed' }       252           146           160           50.57          48.64          16.67       23.601 \r\n    10     {'Purple'      }       139           118           175            30.1          22.54         -20.87       24.672 \r\n    11     {'YellowGreen' }       187           226           110           71.77         -24.13          58.19        15.21 \r\n    12     {'OrangeYellow'}       241           193            78           71.51          18.24          67.37       13.952 \r\n    13     {'Blue'        }        96           131           255           28.37          15.42          -49.8        33.34 \r\n    14     {'Green'       }       118           209           130           54.38         -39.72          32.27       22.461 \r\n    15     {'Red'         }       234           116           114           42.43          51.05          28.62        21.87 \r\n    16     {'Yellow'      }       241           227           105            81.8           2.67          80.41       23.495 \r\n    17     {'Magenta'     }       241           143           221           50.63          51.28         -14.12       23.967 \r\n    18     {'Cyan'        }        94           206           247           49.57         -29.71         -28.32       28.558 \r\n    19     {'White'       }       251           255           255           95.19          -1.03           2.93       5.6635 \r\n    20     {'Neutral8'    }       229           239           246           81.29          -0.57           0.44       13.655 \r\n    21     {'Neutral6.5'  }       203           218           225           66.89          -0.75          -0.06       20.166 \r\n    22     {'Neutral5'    }       165           179           189           50.76          -0.13           0.14        22.69 \r\n    23     {'Neutral3.5'  }       123           136           148           35.63          -0.46          -0.48       21.844 \r\n    24     {'Black'       }        72            83            97           20.64           0.07          -0.46       16.965 \r\n\r\n<\/pre>
Now I just need to figure out how to keep these things out of my garden.<\/p>
This post was adapted from the example \"Create ColorChecker Chart from Test Image\" in the documentation<\/a> for colorChecker<\/tt>.<\/i><\/p>
Copyright 2020 The MathWorks, Inc.<\/i><\/p>