Hi John, Out of curiosity and if it is not much trouble, I would be curious if Luv worked any better than Lab. I think that Luv is supposed to be preferred for monitors and Lab for surfaces but they are generally pretty similar.
Best, Ken Sent from my iPhone ___ Ken Knoblauch Inserm U846 Stem-Cell and Brain Research Institute 18 av du Doyen Lépine 69500 Bron France Tel : 04 72 91 34 77 Fax : 04 72 91 34 61 portable : 06 84 10 64 10 http://www.sbri.fr/members/kenneth-knoblauch.html On 1 juin 2013, at 17:31, "John Fox" <j...@mcmaster.ca> wrote: > Hi Michael, > > Thanks for the Wikipedia tip -- I'd looked there but didn't find this > article. The article explains that the Lab colour space was formulated to > provide uniform perceptual differences between colours, with a JND of > approximately of 2.3. Ken Knoblauch made a similar point. The article goes > on to describe relatively complicated adjustments meant to improve the LAV > distance metric, which are probably overkill for my application. > > I've programmed Lab colour matching as follows, using Euclidean distances > and adapting Kevin Wright's modification of my original code. I used > convertColor(), which Martin Maechler pointed out to me. > > ----------- snip -------------- > > r2c <- function(){ > all.names <- colors() > all.lab <- t(convertColor(t(col2rgb(all.names)), from="sRGB", to="Lab", > scale.in=255)) > find.near <- function(x.lab) { > sq.dist <- colSums((all.lab - x.lab)^2) > rbind(all.names[which.min(sq.dist)], min(sq.dist)) > } > function(cols.hex, near=2.3){ > cols.lab <- t(convertColor(t(col2rgb(cols.hex)), from="sRGB", > to="Lab", scale.in=255)) > cols.near <- apply(cols.lab, 2, find.near) > ifelse(cols.near[2, ] < near^2, cols.near[1, ], cols.hex) > } > } > > rgb2col <- r2c() > > ----------- snip -------------- > > A bit of experimentation suggests that this works better than using (as I > did previously) direct RGB distances, matching more colours to names and > providing (to my eye, with my monitor) perceptually closer matches, though > sometimes with (again to my eye) perceptible differences. Here's an > illustration, adapting one of Kevin's examples: > > ----------- snip -------------- > > cols <- c("#010101", "#EEEEEE", "#AA0000", "#00AA00", "#0000AA", "#AAAA00", > "#AA00AA", "#00AAAA") > (nms <- rgb2col(cols)) > pie(rep(1, 2*length(cols)), labels=c(cols, nms), col=c(cols, nms)) > > ----------- snip -------------- > > Thanks again to everyone who responded to my original, naïve, question. > > Best, > John > >> -----Original Message----- >> From: Michael Friendly [mailto:frien...@yorku.ca] >> Sent: Friday, May 31, 2013 10:24 AM >> To: John Fox >> Cc: r-help@r-project.org; 'Martin Maechler' >> Subject: Re: measuring distances between colours? >> >> Hi John >> This has been an interesting discussion. >> Though you have a solution for your needs, you might be interested in >> this javascript implementation that allows you to visually compare >> color >> distances in various color spaces >> >> http://stevehanov.ca/blog/index.php?id=116 >> >> And, all the theory of color distance is described in >> http://en.wikipedia.org/wiki/Color_difference >> >> PS: This is a very handy function. When I last tried >> aplpack::bagplot(), it was annoying that the colors could *only* >> be specified in hex. >> >> -Michael >> >> >> >> On 5/30/2013 5:14 PM, John Fox wrote: >>> Dear all, >>> >>> My thanks to everyone who addressed my question. I've incorporated >> Eik >>> Vettorazzi's suggestion for improved conversion of hexadecimal RGB >> colours >>> to decimal numbers, and Martin Maechler's hint to look at >> demo(colors). I've >>> loosened the default definition of "close enough" from the latter, >> since the >>> following seems to work well for my purposes. >>> >>> r2c <- function(){ >>> hex2dec <- function(hexnums) { >>> # suggestion of Eik Vettorazzi >>> sapply(strtoi(hexnums, 16L), function(x) x %/% 256^(2:0) %% >> 256) >>> } >>> findMatch <- function(dec.col) { >>> sq.dist <- colSums((hsv - dec.col)^2) >>> rbind(which.min(sq.dist), min(sq.dist)) >>> } >>> colors <- colors() >>> hsv <- rgb2hsv(col2rgb(colors)) >>> function(cols, near=0.25){ >>> cols <- sub("^#", "", toupper(cols)) >>> dec.cols <- rgb2hsv(hex2dec(cols)) >>> which.col <- apply(dec.cols, 2, findMatch) >>> matches <- colors[which.col[1, ]] >>> unmatched <- which.col[2, ] > near^2 >>> matches[unmatched] <- paste("#", cols[unmatched], sep="") >>> matches >>> } >>> } >>> >>> rgb2col <- r2c() >>> >>> For example, >>> >>>> rgb2col(c("010101", "EEEEEE", "AA0000", "00AA00", "0000AA", >> "AAAA00", >>> "AA00AA", "00AAAA")) >>> [1] "black" "gray93" "darkred" "green4" >>> [5] "blue4" "darkgoldenrod" "darkmagenta" "cyan4" >>> >>>> rgb2col(c("010101", "090909", "090000", "000900", "000009", >> "090900", >>> "090009", "000909")) >>> [1] "black" "gray3" "#090000" "#000900" "#000009" "#090900" >>> [7] "#090009" "#000909" >>> >>> Thanks again, >>> John >> >> >> -- >> Michael Friendly Email: friendly AT yorku DOT ca >> Professor, Psychology Dept. & Chair, Quantitative Methods >> York University Voice: 416 736-2100 x66249 Fax: 416 736-5814 >> 4700 Keele Street Web: http://www.datavis.ca >> Toronto, ONT M3J 1P3 CANADA > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
