- All the data that went into making the histogram?
- The positions and heights of the bars?
- Only the image itself?

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Adam Danz
on 22 May 2021

> I need to consider the whole bar chart as a complete area and calculate the percentage of pixel they hold compared to the background, filling the spaces in between.

I don't think there's nearly enough information provided to understand what the question is.

- What defines the background? The x-axis in the first image you shared doesn't even show the axis limit values so the background is not defined.
- Are you refering to a histrogram where there is no space between bars or a bar plot where the width of bars is arbitrary?
- Are you looking for the area under the curve which would require fitting the distribution or are you just interested in individual bar heights?

Scott MacKenzie
on 22 May 2021

Edited: Scott MacKenzie
on 22 May 2021

Your question is a bit of a moving target. The question title refers to a bar plot. The question text refers to a histogram with no mention of a bar plot. Then a bar chart is referred to in the comment. And you didn't answer any of the cyclist's questions.

If you are indeed working with a bar chart, and you want the area under the bars, with the bar widths adjusted to fill the available space, then...

% test data

d = randn(1,1000);

tiledlayout('flow');

nexttile;

y = histcounts(d);

bar(y, 'barwidth', 1);

a1 = sum(y)

set(gca, 'xlim', [0 25]);

nexttile;

x = 1:length(y);

area(x, y);

a2 = polyarea(x,y)

set(gca, 'xlim', [0 25]);

Output:

a1 =

1000

a2 =

945

The area is simply the sum(y) because the width of each bar is 1. a1 (1000) is the exact area under the bars in the bar chart.

The second chart is included since it is similar to the plot in your comment. a2 (945) is the area within a polygon defined by the points in the bar chart.

Adam Danz
on 22 May 2021

> I want to see the difference in histogram analysis of different images by observing a single value.

What single value? If you're refering to the mean color value then you could compute the mean and std for the raw data or you could fit the distribution depending on how you want to interpret the results.

William Rose
on 22 May 2021

If you make a histogram using Matlab's histogram command, for example as follows,

data=randn(1,1000);

h=histogram(data);

then you can determine the area as follows:

histArea=dot(h.Values,(h.BinEdges(2:end)-h.BinEdges(1:end-1)));

The above method multiplies each height by its corresponding width. It gives the right answer even if the bin widths are unequal. In the example I gave, the widths will be equal, but you could specify unequal bin widths in the histogram() function, and the area calculation above will still give the right area.

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