Error using extractLBP​Features>p​arseInputs Expected a string scalar or character vector for the parameter name.

I have faced this error whle I was using extractLBPFeatures:

Error using extractLBPFeatures>parseInputs

Expected a string scalar or character vector for the parameter name.

Error in extractLBPFeatures (line 10)

params = parseInputs(I,varargin{:});

Error in face_recognition_model (line 52)

testFeatures{i} = extractLBPFeatures(img, numNeighbors, radius, numBins);

Code:

%Face Recognition using LRR

%% Load a dataset of grayscale face images

Dataset = imageDatastore('ExtendedYaleB', 'IncludeSubfolders', true, 'LabelSource', 'foldernames');

%% Split the data into training and testing sets

[trainImgs, testImgs] = splitEachLabel(Dataset, 0.7, 'randomized');

%% Extract local patches from the training images using the extractLBPFeatures function

numNeighbors = 8;

radius = 1;

numBins = numNeighbors*(numNeighbors-1)+3;

trainFeatures = cell(numel(trainImgs.Files),1);

for i = 1:numel(trainImgs.Files)

img = readimage(trainImgs,i);

trainFeatures{i} = LBPFeatures(img, numNeighbors, radius, numBins);

end

%% Train the local ridge regression model using the fitrlinear function and local ridge regression

lambda = 1;

span = 0.5;

for i = 1:numel(trainImgs.Files)

features = trainFeatures{i};

label = double(trainImgs.Labels(i));

idx = setdiff(1:numel(trainFeatures),i);

neighbors = vertcat(trainFeatures{idx});

neighborLabels = double(trainImgs.Labels(idx));

mdl = fitrlinear(neighbors,neighborLabels,'Learner','leastsquares','Lambda',lambda);

yhat = zeros(size(features));

for j = 1:size(features,1)

patch = features(j,:);

pred = predict(mdl,patch);

dist = pdist2(patch,neighbors);

w = exp(-dist.^2/(2*span^2));

yhat(j) = sum(w.*pred)/sum(w);

end

trainFeatures{i} = yhat;

end

trainFeatures = cell2mat(trainFeatures);

%% Train the linear regression model on the modified LBP features

mdl = fitrlinear(trainFeatures,double(trainImgs.Labels),'Learner','leastsquares','Lambda',lambda);

%% Save the model to a file

save('face_recognition_model.mat', 'mdl');

%% Extract local patches from the testing images and make predictions using the predict function

testFeatures = cell(numel(testImgs.Files),1);

for i = 1:numel(testImgs.Files)

img = readimage(testImgs,i);

testFeatures{i} = extractLBPFeatures(img, numNeighbors, radius, numBins);

end

testFeatures = cell2mat(testFeatures);

predictions = predict(mdl,testFeatures);

%% Evaluate the performance of the model using the confusionmat and classificationReport functions

confMat = confusionmat(testImgs.Labels,predictions);

classificationReport = classificationReport(testImgs.Labels,predictions);

%% Load the saved model from a file

load('face_recognition_model.mat');

%% Use the loaded model for prediction

testImg = imread('test_image.jpg');

testFeatures = extractLBPFeatures(testImg, numNeighbors, radius, numBins);

prediction = predict(mdl,testFeatures);

Answer 1

[Abhinav Aravindan]

Hi @Abdelrahman,

The “extractLBPFeatures” function accepts the image as the first input argument, and the remaining arguments as Name-Value pairs. For instance:

lbpFeatures = extractLBPFeatures(I,'CellSize',[32 32],'Normalization','None');

The error you are encountering is likely due to the input arguments not being specified as Name-Value pairs. I would suggest replacing your code with the following to resolve the issue:

testFeatures{i} = extractLBPFeatures(img, "NumNeighbors", numNeighbors,"Radius", radius);

As per the documentation, “numBins” is not a valid input argument to the function but is used to reshape the LBP features to access histograms for each individual cell.

Please find attached below the relevant documentation for your reference:

https://www.mathworks.com/help/releases/R2022b/vision/ref/extractlbpfeatures.html#namevaluepairarguments:~:text=numNeighbors%20%3D%208%3B-,numBins,-%3D%20numNeighbors*(numNeighbors%2D1