This affected the early functional design in two ways. Everything in MATLAB was a double-precision matrix. % less than LEVEL and 1 (white) for all other values.Īt that time, the prefix "im" in the function name meant that the function could take more than one image type (indexed, intensity, RGB).Īt this point in the early history of MATLAB, the language really only had one type. BW is 0 (black) for all pixels with luminance % BW = IM2BW(R,G,B,LEVEL) converts the RGB image to black % value less than LEVEL and 1 (white) for all other values. % BW = IM2BW(I,LEVEL) converts the gray level intensity image % than LEVEL and 1 (white) for all other values. % BW is 0 (black) for all pixels with luminance less
% colormap MAP to a black and white intensity image BW. % BW = IM2BW(X,MAP,LEVEL) converts the indexed image X with Here is the help text from that early function: %IM2BW Convert image to black and white by thresholding. That was about the time I interviewed for my job at MathWorks. The function im2bw appeared in Image Processing Toolbox version 1.0, which shipped in early fall 1993. Today I'll start by talking about im2bw and graythresh, two functions that have been in the product for a long time. I want to take advantage of this functionality update to dive into the details of image binarization in a short series of posts.As I promised last time, I'm writing a series about functional designs for image binarization in the Image Processing Toolbox. What's up with this? Why were new functions needed? The toolbox includes two new functions, otsuthresh and adaptthresh, that provide a way to determine the threshold needed to convert a grayscale image into a binary image. The toolbox includes the new function, imbinarize, that converts grayscale images to binary images using global threshold or a locally adaptive threshold. Imbinarize, otsuthresh, and adaptthresh: Threshold images using global and locally adaptive thresholds Now, suddenly, the latest release (R2016a) has introduced an overhaul of binarization. You can think of this as the most fundamental form of image segmentation: separating pixels into two categories (foreground and background).Īside from the introduction of graythresh in the mid-1990s, this area of the Image Processing Toolbox has stayed quietly unchanged. With the very first version of the Image Processing Toolbox, released more than 22 years ago, you could convert a gray-scale image to binary using the function im2bw.
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