The History of Joy Division’s “Unknown Pleasures” Album Art
adamcap.com
adamcap.com
Interesting, but the article misses the point in all kinds of ways. It was common knowledge (at least, to those familiar with Joy Division and Saville's work) that the image itself was appropriated from an original that was in the public domain. The interesting point here is not copyright, but the way in which an image can come to represent a concept such that it gains new meaning. When the intended audience sees this, they think, "Joy Division", not "pulsar". Hence, when you copy the image by way of Saville, you are appropriating the association that he has established. So, this isn't about stealing images, it's about riding on the coat-tails of a talented designer who managed to create a strong brand.
A proper understanding of what's going on here makes this sentiment: "If you ever want to use the image for your own personal benefit, just make sure it’s clear you have no connection with Joy Division, Peter Saville, etc…" pretty shiesty.
http://observer.com/2003/04/national-review-and-shyster-heav...
This was probably the first album that made me consider album art as real works of art. I still love Joy Division's music today and I will never forget this album cover and what I thought when I bought the album (I was a little late to discover Joy Division while Ian Curtis was alive, having discovered them through New Order around 1983 or so). Being interested in Astrophysics (as a lay person) and I believe I read that the band referred to this as "the death of a star" at the time. Love the imagery associated with that.
Great album, great cover art, and great band, I really wish Ian Curtis could have graced us with more from his fantastic mind, I don't think I've ever experienced so much fantastic imagery from any other lyricist.
EDIT: Oh, I forgot, the original CD insert that had this image on it wasn't simple paper as I recall, it was a sort of rough paper (don't know how else to describe it) with the image on it and you could feel the bumps of the lines.
I think it was that, more than even the image by itself, the two together, which really fascinated me. I wish I would have kept that edition of the CD, it was an expensive import at the time and quite original, but I went through a few CD purges back in the 90's and that was a casualty of one of them. :( Oh well. I really wish I would have gotten the vinyl and kept that, but CD's were all the rage back then.
The original sleeve for New Order's Blue Monday was a die-cut sleeve that looked like a large floppy disc. It's routinely told that the sleeve cost more to produce than the entire disc was worth. Factory Records lost money on each copy sold.
Saville also designed Tony Wilson's headstone, which is pretty freaking cool (even though it took a few years to get done)
I'm also glad to see the tombstone is using the Factory Records typeface (at least up top). I wonder if it has a FAC catalog number...
"The headstone doesn't have a Factory catalogue number (that tradition ended with Wilson's coffin, FAC 501)"
http://www.guardian.co.uk/music/2010/oct/26/fitting-headston...
http://machinesdontcare.files.wordpress.com/2010/12/fairligh... http://myblogitsfullofstars.files.wordpress.com/2009/11/fl2x...
The Joy Division style 3-D surface plots were a pretty standard computer graphics thing in the 1970s, often with lines in the Y direction too making a grid. They had the advantage of being pretty easy to program and not requiring a lot of memory - just start drawing lines at the front and keep track of the highest point at each X position. A function such as a damped sinusoid makes a nice image this way.
I'm impressed by the author's tenacity and research, but a library would have really helped him out. Also, I'm puzzled why he thinks the lack of a © on the image itself matters - magazines usually have something like "Entire contents copyright" in the masthead.
¹ http://books.google.com/books?id=IWxyanKoRUoC&lpg=PA104&...
Apparently it was done with some sort of oscillograph.
So how come the peaks hide the drawings behind it?
Ok, thinking about this, if the drawing is done all at the same time, (like a signal FFT from the 60's) then the lower drawing device hits the upper drawing device (if the signal is bigger) hence making both trace the same thing.
To give you an idea of what was possible in 1971, the arcade machine Computer Space was released that year: http://en.wikipedia.org/wiki/Computer_Space
This article does actually explain this, but I can forgive you for not getting that far as it's the very last item on his blog and appears only to have been mentioned as an after thought.
I think you've misunderstood what we are talking about - the method by which the graphic was created. Which I assume to have been a plotter fed instructions by a program that removed hidden lines from the graphs.
EIGHTY SUCCESSIVE PERIODS of the first pulsar observed,
CP1919 (Cambridge pulsar at 19 hours 19 minutes right
ascension), are stacked on top of one another using the
average period of 1.33730 seconds in this computer-generated
illustration produced at the Arecibo Radio Observatory in
Puerto Rico.I'd love to see the t-shirt produced, and the reaction from the record companies.
http://24.media.tumblr.com/b2d0e6039db4d09a5b543bd121012321/...
It seems that the options for getting artistic content for your products (websites/books/games/album covers) these days are limited. Either you go get something off istock photo, or your rip from google images hoping that the original owner doesn't notice.
Wouldn't it be nice to have a marketplace for art? Or some sort of protocol for tracking down who created what?
The business model for the company would be that of intermediary -- i find who the copyright belongs to and skim a keep a percentage of the royalty.
Better art and no fear of copyright infringement for clients + better paid artists = win win.
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heuh... it looks a bit horrible in ASCII art ;-) import random
import math
canvh = 40
canvw = 60
tracecount = 16
canvas = [[' ' for col in xrange(canvw)] for row in xrange(canvh)]
def randomtrace():
sigma = random.uniform(4, 20)
mu = random.gauss(canvw/2, canvw/20)
k = canvw / (sigma * math.sqrt(2*math.pi))
s = -1.0 / (2 * sigma * sigma)
amp = 2.0
tr = [amp * k * math.exp(s * (x - mu)*(x - mu)) for x in xrange(canvw)]
# TODO: Random permutations, or Perlin noise.
return tr
for t in range(tracecount):
if t == 0 or t == tracecount - 1:
continue
y = t * canvh / tracecount
trace = randomtrace()
for x, t in enumerate(trace):
t = int(t)
top = y - t
if top >= 0:
canvas[top][x] = '-'
for i in range(t):
top += 1
if top >= 0:
canvas[top][x] = ' '
for row in canvas:
line = "".join(row)
print " ", line ⠶⠾⣿⡿⠟⠁⠀⠀⠀⢀⣾⠁⠀⢹⡇⠀⠀⠀⠀⠀⢀⡾⠁⠀⠀⠀⠸⣧⣠⣤⣄⡀⠀⠀⠀⠀⠀⠀⠙⢷⣄⠀⢀⣠⣤⣴⠞⠁⠀⠘⠷⣦⡀⠀⠀⣩⡿⢿⣿⣓⡶⠶⠶⠶⢦⣤
⣤⡼⠋⠀⠀⠀⠀⠀⢠⣾⡟⠀⠀⠀⢿⡀⠀⠀⢠⡾⠛⠁⣤⣤⣄⡀⠀⠈⢻⣄⠈⠛⢷⣄⣀⢀⣠⡶⠶⢶⡝⠛⠛⠁⠀⠀⠀⠀⠀⣀⣠⣼⠿⣷⣟⠉⠀⠀⠈⢻⣿⠶⣤⡤⠤⣤
⠟⠀⠀⠀⠀⠀⢀⣴⠏⣿⠁⠀⠀⠀⠘⣷⡶⠶⢿⣄⠀⢸⡇⠀⠈⢻⣄⣀⠀⠙⢷⣄⠀⠙⠻⠛⠉⠀⠀⠀⠻⣾⣟⠛⠛⠛⠛⠛⠛⠉⠉⠀⠀⠀⠉⠛⠛⠳⠶⠶⣭⣿⣦⣤⣤⣄
⣠⣤⣤⣴⡶⠶⠛⠁⣸⡇⠀⠀⠀⠀⠀⢸⣇⠀⠀⢹⣶⡟⠀⠀⠀⠈⢿⡙⠷⣄⠀⠙⢷⣄⡀⠀⠀⠀⠀⠀⠀⠀⠙⠳⣦⣄⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠙⠷⣬
⣁⡀⣀⣀⣤⣴⠶⣾⣿⠃⠀⠀⠀⠀⠀⠀⢿⣄⣠⡟⠁⠀⠀⠀⠀⠀⠘⠿⣿⠻⠷⠲⣦⡉⠻⠶⠶⠶⠶⣦⣤⣄⡀⢀⣠⡿⠛⠻⣿⠛⠲⠶⠛⠛⠛⠛⢶⣄⠀⠀⠀⠀⠀⠀⠀⠀
⠉⠉⠉⠁⠀⠀⣰⢏⣿⠀⠀⠀⠀⠀⠀⠀⠈⣿⡏⠀⢠⡶⣦⡀⠀⠀⠀⠀⠙⢷⣄⣀⣈⣝⣿⣷⣄⣀⣀⣀⡀⠈⢻⡿⠁⠀⠀⠀⠹⢷⡶⠶⠾⠛⢦⣤⣤⣝⣿⣛⠛⠛⠲⠶⠶⠤
⣛⣻⣿⣯⣽⣿⠋⣼⠃⠀⠀⠀⠀⠀⠀⠀⠀⠸⣇⠀⣿⠁⠈⢷⡀⠀⠀⠀⠀⠀⠉⠉⠁⠈⠛⠿⣯⣍⡙⠛⢛⣿⠟⠀⠀⠀⠀⠀⠀⠈⢿⡄⠀⠀⠀⠀⠀⠉⠙⠉⠛⠻⢿⣶⡶⠛
⠉⢀⣀⣤⠟⠁⢸⡏⠀⠀⠀⠀⠀⠀⠀⢠⡶⣦⣻⣼⡏⠀⠀⠘⣧⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠛⠶⠟⠁⠀⠀⠀⠀⠀⠀⠀⠀⠈⠻⣆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠻⢶
⠛⠋⠉⠀⢀⣴⡟⠀⠀⠀⠀⠀⠀⠀⣾⠋⠀⠈⢷⡿⠀⠀⠀⠀⠘⣧⣀⣠⡴⠶⠞⠻⣦⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠹⣿⡛⠛⠶⠶⠶⣤⣄⠀⠀⠀⠀⠀
⣤⡴⠖⠛⣫⡟⠀⠀⠀⣀⠀⠀⠀⣸⠇⠀⠀⠀⣼⠇⠀⠀⠀⠀⠀⠘⣿⡋⠀⠀⠀⠀⠈⠻⣦⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⣀⠀⢀⣈⣿⡖⢶⣤⣤⣀⠉⠛⠛⠛⠷⣤
⣀⣴⠟⢻⡿⠀⠀⠀⣰⠟⢷⣄⡼⠋⠀⠀⣀⣴⠏⠀⠀⠀⠀⠀⠀⠀⠸⣧⠀⠀⠀⠀⠀⠀⠈⠛⢿⣿⡛⠓⠶⠶⢶⣲⡶⠲⠶⠚⠛⠉⣙⡿⠿⠋⠉⠙⠋⠛⢦⣝⢷⣄⣀⣀⡀⠀
⠉⢀⣴⠟⠀⠀⠀⣼⠃⠀⠀⢻⣇⠀⢠⡾⠋⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠙⠿⣶⣶⢦⣤⣤⣤⣤⣀⣈⣙⣷⣶⣶⡿⠋⣙⣷⣶⠶⠶⢛⣯⡤⣤⡀⠀⠀⠀⠀⠀⠙⠷⣭⣻⢯⣭⣭
⡶⠋⠁⠀⠀⢀⣸⠏⠀⠀⠀⠀⢻⣦⡾⠁⠀⠀⠀⠀⠀⠀⢀⣠⣴⡶⠛⠛⠶⠞⠛⠛⢷⣶⠶⠶⠶⠯⣭⣀⡀⢀⣴⠟⠉⠻⢿⣿⡶⠏⠀⠀⠈⢻⣆⠀⠀⠀⠀⠀⠀⠈⠙⠛⠳⢶
⠀⣀⣀⣴⠞⣿⠏⠀⠀⠀⠀⠀⠀⠉⠻⢦⣤⣤⠶⠖⠲⢾⣿⠿⠋⠀⠀⠀⠀⠀⠀⠀⠀⠙⣷⣄⣤⣤⣤⣽⠟⠋⠀⠀⠀⠀⠀⠀⠀⠀⢀⣴⠛⠷⣿⣟⠛⠛⠛⠳⣦⣄⣀⣀⡀⠀
⠛⠉⢁⣠⡞⠁⠀⠀⠀⢀⣀⣀⣀⣀⣠⣴⠾⠛⢳⣤⣴⠟⠛⠷⣦⣠⣤⡀⠀⠀⠀⠀⠀⠀⠀⠙⠷⣤⣀⣀⠀⠀⠀⠀⠀⠀⠀⣠⡴⠟⠛⠁⠀⠀⠀⠙⢷⣄⣀⠀⠀⠈⠉⠉⠉⠉
⠛⠛⣻⠟⠀⣠⣤⣤⠶⠛⠉⠉⠉⠉⠁⠀⠀⣠⡾⠋⠀⠀⠀⠀⣾⠃⠈⠛⢶⣦⠶⢤⣤⣤⣀⠀⠀⠈⠉⠉⠙⠷⠶⠶⠶⠾⠛⠉⠀⠀⠀⠀⠀⠀⠀⠀⠀⠙⢿⣽⣟⠛⠓⠶⠶⢦
⢛⣿⢏⣴⠛⠁⠀⠀⠀⠀⠀⠀⠀⠀⢀⣠⡾⠋⠀⠀⠀⠀⠀⣼⣷⣤⡀⠀⠀⠙⢷⣄⠀⠀⠙⠛⠶⠶⠛⠳⠾⠳⠶⣤⣄⣀⣀⣀⣀⣀⣴⠶⠶⠶⣤⣀⣀⡀⠈⠙⢿⣿⣟⣛⣛⠓
⣛⣵⠏⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⣴⠟⢁⣤⣤⡀⠀⢀⣤⡾⠋⠀⠈⢿⡄⠀⠀⠀⢻⣶⣤⣤⣤⣄⣀⠀⣀⣠⣤⣄⠀⠈⠉⠉⠉⠉⠉⠀⠀⠀⠀⠀⠉⠉⠙⠳⣦⣤⣄⣀⣉⠉⠛
⠋⠀⠀⠀⠀⢀⣀⣀⡴⢶⡶⢿⡿⢛⣷⣿⢻⡟⠿⠷⣿⡟⠁⠀⠀⠀⠈⣿⡄⠀⠀⠀⠉⠉⠛⠷⣬⣍⣛⠉⠁⠀⢉⣿⣷⣤⣤⣤⣤⣤⡴⠶⣦⣀⣀⣀⣀⣀⠀⠀⠀⠀⠉⠙⠛⠶
⣤⣤⣤⣤⣶⠿⢿⣿⡾⠋⠀⠈⠙⠋⣱⡟⠀⢿⡄⢠⡿⠁⠀⠀⠀⠀⠀⠘⢷⣄⠀⠀⠀⠀⠀⠀⠀⠉⠙⠛⠛⠛⠋⠁⠀⠀⠀⠁⢀⣠⣴⠶⠛⠉⠉⠉⠉⠙⢷⣄⣀⣀⡀⠀⢀⠀
⣤⡴⠞⠋⠁⢠⣿⡴⠞⠶⠶⠶⠞⢻⡟⠀⠀⠈⣿⡟⠀⠀⠀⠀⠀⠀⠀⠀⠀⠻⣦⣤⣄⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⣤⣴⠶⠾⠛⠉⠀⠀⠀⠀⠀⠀⠀⠀⠀⠙⢿⣭⣙⡛⠋⢙
⣀⣠⣤⠴⠶⣻⡟⠀⠀⠀⠀⠀⠀⣾⠃⠀⠀⠀⢹⣧⣤⡀⠀⠀⢀⣤⠴⠶⢦⣄⠙⠷⣍⣉⡛⡛⠛⠛⠻⣿⣿⣿⣛⣋⠁⣀⣀⣠⣤⣤⣴⠶⠿⣶⡶⠶⣤⣤⣤⣄⡀⠀⠈⠉⠛⠿
⠉⣁⣤⠶⠞⠋⠀⠀⠀⠀⠀⣀⣾⡇⠀⠀⠀⠀⠈⢿⡌⠙⢷⣴⣿⠁⠀⠀⠀⠙⢷⣤⣈⠉⠉⠙⠷⣦⣤⣀⠈⠉⠉⣉⣋⣩⡿⠿⠞⠋⠀⠀⠀⠘⢷⣦⠀⠀⠀⠉⠙⠳⢦⣤⣄⣀
⠋⠉⠁⠀⠀⠀⠀⢀⣤⠶⣞⣯⣿⠃⠀⠀⠀⠀⠀⢸⣧⠀⠀⠀⠙⢷⣄⠀⢀⣀⣀⡈⠙⠛⠛⠻⠶⣦⣀⡉⢛⣻⣿⠟⠛⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠙⠷⣦⡀⠀⠀⠀⠀⠀⠉⠙
⠶⠶⠞⢛⣩⣽⠿⠛⣻⣿⣿⢿⡏⠀⠀⠀⠀⠀⠀⠀⢿⡄⠀⠀⠀⠀⠘⠿⣯⡉⠉⠻⢶⣄⠀⠀⠀⠀⠉⠙⠛⠉⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠉⠛⢷⣶⣶⠶⢤⡤⢤
⠛⠒⠛⠋⠁⣀⣤⣾⣵⡟⢡⡿⠀⠀⠀⠀⠀⠀⠀⠀⠈⣿⣤⠶⠾⠶⠶⢦⣬⡛⠷⣤⣀⣙⣻⢿⣿⣛⠛⠛⠶⣤⣤⡤⠶⢶⣶⣾⣛⣛⡛⠛⠛⠻⠛⠛⠳⣤⡀⠀⠀⠈⠛⠛⠶⠶
⠶⠶⣶⣶⠟⠛⠉⣡⡟⠀⣼⠇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠘⣷⡀⠀⢀⣴⣦⠈⠛⢷⣬⣙⣋⠉⠻⠶⠿⠷⣦⣤⡼⠋⠀⠀⠀⠀⠈⠉⠋⠻⣦⣤⣤⣄⣀⣀⠈⠛⠷⠶⠤⠶⠶⢤⣄
⠾⠛⠉⠀⣀⣤⢾⡿⠁⣰⡟⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠻⣦⡾⠃⢻⡄⢀⣀⣬⡉⠉⠛⠷⢶⠶⠶⠛⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢻⣄⡈⠉⠉⠙⠛⠳⠶⢦⣤⣤⣤⣌
⣤⡴⠶⠞⠋⢡⡞⠁⢠⡟⠀⢀⣴⣦⡴⠶⠶⣦⣀⣀⣀⣀⣤⢶⡟⠀⠀⠘⣿⠋⠉⠈⠛⢷⣄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣈⣛⣿⣛⣶⠶⠦⢤⣤⣤⣤⣀⣈
⣀⣀⣀⣀⣴⡟⠀⣠⡿⠀⢀⣾⠃⢸⣇⠀⠀⠈⠛⢿⣌⠉⠀⣼⠇⠀⠀⠀⢹⣧⠀⠀⠀⠈⠛⠳⢶⣄⠀⠀⠀⠀⢀⣴⠶⢶⣄⣀⣤⡤⣴⡶⠟⠻⢿⣭⣉⠉⠻⣦⣀⣀⠀⠀⠈⠉ import pylab
import scipy
def gaussian(x, centre, xscale, height):
return height * scipy.exp(-(2.*xscale*(x-centre))**2)
def triangle(x, centre, xscale, height):
y = height * (1. - scipy.absolute(xscale*(x-centre)))
return (y>0) * y
x = scipy.linspace(0., 1., 1501)
shape = triangle#gaussian#
def generate_noise(x, num_bumps, centre_min, centre_max, xscale_min,
xscale_max, height_min, height_max, shape=shape):
y = scipy.zeros_like(x)
for i in xrange(num_bumps):
centre = centre_min + (centre_max-centre_min)*scipy.rand()
xscale = xscale_min + (xscale_max-xscale_min)*scipy.rand()
height = height_min + (height_max-height_min)*scipy.rand()
print centre, xscale, height
y += shape(x, centre, xscale, height)
return y
def generate_line(x):
y = scipy.zeros_like(x)
y += generate_noise(x, 100, 0., 1., 0., 300., 0., .003)
y += generate_noise(x, 10, .25, .75, 20., 30., 0., .03)
y += generate_noise(x, 10, .29, .45, 20., 30., 0., .03)
return y
num_lines = 85
line_gap = .015
for i in xrange(num_lines):
base_line = (num_lines-i)*line_gap
y = base_line + generate_line(x)
poly = pylab.Polygon([(x[0], base_line)]+zip(x, y)+[(x[-1], base_line)],
facecolor='k', edgecolor='none', zorder=i)
pylab.gca().add_patch(poly)
pylab.plot(x, y, 'w', linewidth=2, zorder=i+.5)
pylab.gcf().patch.set_facecolor('black')
pylab.gca().set_axis_bgcolor('k')
pylab.axis('equal')
pylab.gcf().set_size_inches(8., 8.)
pylab.savefig('pulsar.png', facecolor=pylab.gcf().get_facecolor(),
edgecolor='none', dpi=150)Here's an animated, interactive visualization that looks like the Joy Division album cover, based on d3.js https://github.com/daliwali/unknown_pleasures
There's no attribution credit for the image, though many other images in the book have such credits.
The caption does note, however, that the pulsar has a period of 1.337 seconds. I believe this makes it quite leet.
I remember when the album came out I immediately recognized the image, but I had no idea they had lifted it directly from the book itself. Now I wish I hadn't cut the picture out and taped it to the wall. :)