Introduction


Figure 1

Bacteria colony

Figure 2

Colonies counted

Figure 3

Bacteria colony

Image Basics


Figure 1

Original size image

Figure 2

Enlarged image area

Figure 3

Image of 8

Figure 4

Image of 0

Figure 5

Cartesian coordinate system

Figure 6

Image coordinate system

Figure 7

Left-hand coordinate system

Figure 8

Image of 5

Figure 9

Image of three colours

Figure 10

Image in greyscale

Figure 11

Image of checkerboard

Figure 12

Image of red channel

Figure 13

Image of green channel

Figure 14

Image of blue channel

Figure 15

RGB colour table

Figure 16

Original image

Figure 17

Enlarged, uncompressed

Figure 18

Enlarged, compressed

Figure 19

Uncompressed histogram

Working with scikit-image


Figure 1

Root cluster image

Figure 2

Thresholded root image

Figure 3

Su-Do-Ku puzzle

Figure 4

Modified Su-Do-Ku puzzle

Figure 5

Whiteboard image

Figure 6

Whiteboard coordinates

Figure 7

"Erased" whiteboard

Drawing and Bitwise Operations


Figure 1

Maize seedlings

Figure 2

Here is what our constructed mask looks like: Maize image mask


Figure 3

Sample shapes

Figure 4

Applied mask

Figure 5

Remote control image

Figure 6

Remote control masked

Figure 7

96-well plate

Figure 8

Masked 96-well plate

Creating Histograms


Figure 1

We will start with grayscale images, and then move on to colour images. We will use this image of a plant seedling as an example: Plant seedling


Figure 2

Plant seedling

Figure 3

Plant seedling histogram

Figure 4

Grayscale histogram of masked area

Figure 5

Colour histogram

Figure 6

Well plate image

Figure 7

Masked well plate

Figure 8

Well plate histogram

Blurring Images


Figure 1

Cat image

Figure 2

Cat eye pixels

Figure 3

A Gaussian function maps random variables into a normal distribution or “Bell Curve”. Gaussian function


Figure 4

2D Gaussian function

Figure 5

2D Gaussian function

Figure 6

Image corner pixels

Figure 7

Image multiplication

Figure 8

Blur demo animation

Figure 9

Original image

Figure 10

Blurred image

Figure 11

Bacteria colony
Graysacle version of the Petri dish image

Figure 12

Bacteria colony image with selected pixels marker
Grayscale Petri dish image marking selected pixels for profiling

Figure 13

Pixel intensities profile in original image
Intensities profile line plot of pixels along Y=150 in original image

Figure 14

Pixel intensities profile in blurred image
Intensities profile of pixels along Y=150 in blurred image

Figure 15

3D surface plot showing pixel intensities across the whole example Petri dish image before blurring
A 3D plot of pixel intensities across the whole Petri dish image before blurring. Explore how this plot was created with matplotlib. Image credit: Carlos H Brandt.

Figure 16

3D surface plot illustrating the smoothing effect on pixel intensities across the whole example Petri dish image after blurring
A 3D plot of pixel intensities after Gaussian blurring of the Petri dish image. Note the ‘smoothing’ effect on the pixel intensities of the colonies in the image, and the ‘flattening’ of the background noise at relatively low pixel intensities throughout the image. Explore how this plot was created with matplotlib. Image credit: Carlos H Brandt.

Figure 17

Rectangular kernel blurred image

Thresholding


Figure 1

Image with geometric shapes on white background

Figure 2

Grayscale image of the geometric shapes

Figure 3

Grayscale histogram of the geometric shapes image

Figure 4

Binary mask of the geometric shapes created by thresholding

Figure 5

Selected shapes after applying binary mask

Figure 6

Another image with geometric shapes on white background

Figure 7

Grayscale histogram of the second geometric shapes image

Figure 8

Binary mask created by thresholding the second geometric shapes image

Figure 9

Selected shapes after applying binary mask to the second geometric shapes image

Figure 10

Image of a maize root

Figure 11

Grayscale histogram of the maize root image

Figure 12

Binary mask of the maize root system

Figure 13

Masked selection of the maize root system

Figure 14

Four images of maize roots

Figure 15

Binary masks of the four maize root images

Figure 16

Improved binary masks of the four maize root images

Figure 17

Image of bacteria colonies in a petri dish

Figure 18

Grayscale histogram of the bacteria colonies image

Figure 19

Binary mask of the bacteria colonies image

Connected Component Analysis


Figure 1

Original shapes image

Figure 2

Mask created by thresholding

Figure 3

Labeled objects

Figure 4

shapes-01.jpg mask detail

Figure 5

Histogram of object areas

Figure 6

Objects filtered by area

Figure 7

Objects colored by area

Capstone Challenge


Figure 1

Colony image 1

Figure 2

Colony image 2

Figure 3

Colony image 3

Figure 4

Sample morphometric output

Figure 5

Colony image 1

Figure 6

Gray Colonies

Figure 7

Histogram image

Figure 8

Colony mask image

Figure 9

Sample morphometric output

Figure 10

Colony 1 outputColony 2 outputColony 3 output


Multidimensional data


Figure 1

colonies napari ss

Figure 2

cells napari ss

Figure 3

cells seperate napari ss

Figure 4

nuclei napari ss

Figure 5

shapes napari ss

Figure 6

colonies napari 3 ss

Figure 7

cell3d slice napari ss

Figure 8

cell3d volume napari ss

Figure 9

cell3d volume napari ss

Figure 10

cell3d labels napari ss

Figure 11

cell timelapse napari ss

Figure 12

cell timelapse mean plot ss

Figure 13

cell timelapse mask napari ss

Figure 14

cell timelapse area plot ss

Figure 15

cell timelapse tracking napari ss

Figure 16

cell timelapse tracking plot ss