Issue in recognising multiple objects in an Image

2017 1 21
2 个回答
回答已采纳
更新时间：2018 5 26
4 次查看（30 天）

0 个投票

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 个评论
显示 2更早的评论 隐藏 2更早的评论

Rohan Gupta
Rohan Gupta 2017-1-23
Hello Sir, I have attached the folder consisting of some of the train images and one test image. The knn classifier classifies the test image as either orange or apple, I am really struggling to find a way to make classifier identify both orange and apple in an image. It would be really grateful, if you can help me. Given below is my code.
clc; clear all;
imfile = dir('C:\Users\JTS_10\Desktop\Fruits\train_imag\train\*.jpg'); imfile1 = dir('C:\Users\JTS_10\Desktop\Fruits\test_imag\test\*.jpg');
a = struct2cell(imfile); train_lists = {a(1,:)};
d = struct2cell(imfile1); test_lists = {d(1,:)};
g = zeros(length(imfile),512);
l = {'Apple';'Orange'}; train_label = [repmat(l(1),10,1);repmat(l(2),10,1)]; test_label = [repmat(l(1),2,1);repmat(l(2),2,1)];
%% Extract features from Train Images
for i = 1:length(imfile) img = strcat('C:\Users\JTS_10\Desktop\Fruits\train_imag\train\',imfile(i).name); I1 = imread(img);
% Parameters:
param.imageSize = [256 256]; % it works also with non-square images
param.orientationsPerScale = [8 8 8 8];
param.numberBlocks = 4;
param.fc_prefilt = 4;
[gist1, param] = LMgist(I1, '', param);
g(i,:) = gist1;
end
%% Extract features from Test Image
img1 = strcat('C:\Users\JTS_10\Desktop\Fruits\test_imag\test\',imfile1(i).name);
I1 = imread(img1);
imshow(I1);
% Parameters:
param.imageSize = [256 256]; % it works also with non-square images
param.orientationsPerScale = [8 8 8 8];
param.numberBlocks = 4;
param.fc_prefilt = 4;
[gist2, param] = LMgist(I1, '', param);
class = knnclassify(gist2,g,train_label);
Rohan Gupta
Rohan Gupta 2017-1-25
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 2018-5-26
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.

请先登录，再进行评论。

请先登录，再回答此问题。

 采纳的回答

Image Analyst
Image Analyst 2017-1-25

0 个投票

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 个评论
显示 1更早的评论 隐藏 1更早的评论

Rohan Gupta
Rohan Gupta 2017-1-27
You are right Sir, I should simply look for color. But, in my single test image there will be 3 or 4 fruits. So, how will the classifier detect all fruits in the test image.
Image Analyst
Image Analyst 2017-1-27
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

请先登录，再进行评论。

更多回答（1 个）

Takuji Fukumoto
Takuji Fukumoto 2017-1-25

0 个投票

Why don't you use R-CNN? http://jp.mathworks.com/help/vision/ref/trainrcnnobjectdetector.html
I think you should cut block from a whole image and slide it for recognition if you want to use that classification.

3 个评论
显示 1更早的评论 隐藏 1更早的评论

Rohan Gupta
Rohan Gupta 2017-1-25
Could you please elaborate. What do you mean by cutting a block from whole image?
Takuji Fukumoto
Takuji Fukumoto 2017-1-25
编辑：Takuji Fukumoto 2017-1-25
I mean it can work if you create 'search window'. The search window is used in some detector algorithm.
https://www.mathworks.com/help/releases/R2016b/vision/ref/vision.peopledetector-class.html
RCNN find something like object first and then use classifier.
Rohan Gupta
Rohan Gupta 2017-1-27
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.

请先登录，再进行评论。

类别

在 帮助中心 和 File Exchange 中查找有关 Object Detection 的更多信息

产品

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by