Issue in recognising multiple objects in an Image

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I have images of Apples as well as of Oranges, which I am using as training images. The test image is an image consisting of both apple and orange. I am using GIST descriptor for feature extraction. When I train the classifier using extracted features, it gives an output as apple or orange for the test image. I have a query, as how can I make classifier recognise both of them in the test image. I am using KNN classifier
  4 Comments
Rohan Gupta
Rohan Gupta on 25 Jan 2017
It would be really helpful if someone would help me out with this problem. I would like to know if my approach is correct or not.
william  pyae
william pyae on 26 May 2018
Hi Rohan, I'm doing a similar project as yours. Could you able to post all your matlab code in the file exchange? I would like to take references from your project. Thank you so much.

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Accepted Answer

Image Analyst
Image Analyst on 25 Jan 2017
Why not simply look at the color? Just convert to HSV color space, mask out the background and look at the amount of orange in the image. If there's more orange than non-orange, it's an orange.
  3 Comments
Image Analyst
Image Analyst on 27 Jan 2017
regionprops() will tell you the hue of every single region in the image. Once you've made a determination, you can assign a string with the name of the fruit. Like
props = regionprops(binaryImage, hueImage, 'MeanIntensity');
for k = 1 : length(props)
thisHue = props(k).MeanIntensity
if thisHue < 0.1 % or whatever
fruitType{k} = 'Apple'
else
fruitType{k} = 'Orange'
end
end

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More Answers (1)

Takuji Fukumoto
Takuji Fukumoto on 25 Jan 2017
I think you should cut block from a whole image and slide it for recognition if you want to use that classification.
  3 Comments
Takuji Fukumoto
Takuji Fukumoto on 25 Jan 2017
Edited: Takuji Fukumoto on 25 Jan 2017
I mean it can work if you create 'search window'. The search window is used in some detector algorithm.
RCNN find something like object first and then use classifier.
Rohan Gupta
Rohan Gupta on 27 Jan 2017
I am not suppose to use RCNN or CNN for this application. Is there any other way. By the way thank you for your valuable inputs. It would be really helpful, if you could help me out further.
The single test image will have 3 or 4 fruits, How can I detect all of them?
Features of each fruits can be extracted using color as it's feature (during training), but when I train KNN classifier and give it a test image, it will give only one output (i.e orange or apple). It won't tell me the names of all the fruits present in the image.

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