63 - Image Segmentation using traditional machine learning Part1 - FeatureExtraction

This is part 1 of the 5 part series tutorials that covers the topic of image segmentation using feature engineering and random forest classification. In this tutorial you'll learn how to extract features from your training images and organize the data in Pandas data frame to be ready for machine learning classification.

[morgomi]

I would like to thank you with all my heart. Not for only this video but for all of your videos.

[sali-math-arts]

Very very excellent and understandable videos - and in my case very interesting how other disciplines use ML /AI /deep learning. Thank you so much for sharing !! EXCELLENT 🙂

[saidielhoussaine]

i enjoy watching this video, thank you for sharing

[inhibited]

I was asking the doctor about my father's mri and he showed me photos. they suspected he had some cancer hanging off his appendix long ago, but they could only guess. I suppose this method could be used to make data for a prediction. OMG what a ton of work it would be.

[bobbysingh]

Hi Sreeni. Concerning the extracted features which are then to be used in the "Traditional Machine Learning" approach, do the features not need to be normalized? When playing around on my own image, the max pixel intensity is 255. However, the maximum value returned for the Sobel filter is 0.73. Does the machine learning model not need the features to be normalized to the name range as every other feature, including pixel intensity? And if not, when do we need to worry about normalizing features? Thanks

[alexiscarlier]

Sorry, I have one more question. I see that you apply the gabor filters on img2 that has already been reshape. Is it the same as apply it on the 2D img?

[genievickery]

Thank you so much for this video series, they are incredibly informative. I was wondering why it is important to first convert the image to greyscale? I was thinking the original pixel values might be more informative? (eg if an index such as NDVI has been calculated per-pixel, and the resulting image used) Thanks for any help with this!

[zeeshanpatel]

Hi, thank you for this great tutorial. I was wondering how you developed your labeled image in this video. Did you already apply some histogram segmentation to it beforehand?

[sladayalnz]

if you have 2 Images of 1kx1k how would you determine your dataframe? just concatenating the second image pixel values and other filters to the initial one would work for it ?

[holthuizenoemoet]

Greate video, what do you uses to create the image masks?

[masbro]

may i ask about the labeled image 19:10, what do you mean by labeled image? is it the name? is it the same as the train image? is it just showing the original image pixel? could we use other ground truth, e.g. writer's id.? thank you sir.

[centralprocessingunit]

"MemoryError: could not allocate 268435456 bytes"
is the program meant to need 256 megabytes for one image?

[rs]

great tutorial. Can you make a video on how to combine hand-crafted features with CNN? I want to ask whether the CNN features can encode angles information similar to HOG or Gabor filters. It will be great if we can combine them

[AbdulQayyum-kdgf]

Great explanation. Could you share the training image file and label file images?

[centralprocessingunit]

how to do this without having to change the colours to grey and just keeping the original image?

[aditichawla]

The above code is throwing this error : "Length of values (1019904) does not match length of index (3059712)". How to fix this?

[johnchristie]

Sir, should I convert the image to Gray? I need the RGB color feature to be extracted. How it come?
Thanks

[veeraazhagan]

Thanks for your videos sir
I got an error like length of values does not match length of index while adding the color image's data frame to original df. Am using brain mri image.
While colouring the image I just colored half portion of image not all portion as u did. Could u help me out with solving this error.

[inhibited]

I tried manually highlighting my data minimally. Equivalent to highlighting only the white spots as yellow on the photos, leaving background blue, highlighting everything else as green and ran the program. Lets say I just needed to be able to forecast where the white spots were only. I got 40% accuracy and the segmented pictures in video 66 or 67 were pathetic. Just in case anyone wants to try the approach.

[Hans-okrc]

How do I get the label image, is it really one pixel label? It will be very time consuming