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Study and

Implementation of

Watershed Algorithm

using MATLAB

Supervisor– Prof. Sanjeev Kumar By– Mukul Jindal

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Watershed Algorithm

The watershed transformation is a technique for

segmenting digital images that uses a type of

region growing method based on an image gradient. It

thus effectively combines elements from

both the discontinuity and similarity methods described

below.

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What is Image Segmentation

The goal of image segmentation is to reduce the number of colours in the input

reference image and then group neighbouring pixels of similar colour together to

form bounded segments

Segmentation subdivides an image into its constituent regions or groups.

The level to which the subdivision is carried depends on the problem being

solved.

That is, segmentation should stop when the objects of interest in an application

have been isolated.

e.g. automated inspection of electronic assemblies; specific anomalies; missing

components or broken connection paths.

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Image Segmentation

algorithm

It is based on two basic properties of intensity values :

discontinuity and similarity

First Category : Abrupt changes in intensity.

Second Category : Partitioning of regions which are

similar according to a set of predefined criteria. e.g.

thresholding, region growing, region splitting and merging.

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First Category is further subdivided into-

•Points

•Lines

•Edges

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Detection of discontinuities

Points, lines, edges

The most common way

R = w1*z1 + w2*z2 + ……+ w9*z9

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Point detection

R T

T = Threshold

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Point detection

(b) X-ray image

of a turbine blade

with porosity

(c) Result of

point detection

mask

(d) Result of point

detection mask

with threshold

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Line detection

– A Suitable Mask in desired direction

– Thresholding

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• Example:

Line detection

-45º Mask Thresholding

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Edge Detection

– Two Mathematical model

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Edge Detection

Second derivative

First

derivative

Gray level

profile

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Gradient Operators

X-directionY-direction

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Diagonal Edge

45-Direction-45-Direction

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Diagonal edge detection

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Things done so far

• Read about different Image Segmentation processes.

• Working my way towards implementing Watershed

algorithm using MATLAB.

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Things to be done

• Use preprocessing method to be implemented on

images.

• Implement Watershed Algorithm

• Analyse and record the difference after processing.

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Test Result Expected from Watershed

Algorithm

Test image After Watershed Algorithm

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References -

• Paul R. Hill. Wavelet Based Texture Analysis and

Segmentation for Image Retrieval and Fusion. PhD thesis,

University of Bristol, March 2002.

• Richard E. Woods and R.C. Gonzalez. Digital Image

Processing. Pearson Education, 2005.

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