function vec = genFeatureVec(img,minc,maxc)
    bins = 16;
    ncnls = 8;
    secs = 6;
    cnls = zeros(size(img,1), size(img,2),ncnls);
    cnls(:,:,1:3) = img;
    cnls(:,:,4:6) = rgb2ycbcr(img);
    hsv = rgb2hsv(img);
    cnls(:,:,7:8) = hsv(:,:,1:2);
    for i=1:ncnls
        cnls(:,:,i) = histeq(cnls(:,:,i));
    end
    % Schmid
    scVec=[
        1,2;
        1,4;
        2,4;
        1,6;
        2,6;
        3,6;
        1,8;
        2,8;
        3,8;
        1,10;
        2,10;
        3,10;
        4,10];
    gbVec = [
        0.3,0,4,2;
        0.3,0,8,2;
        0.4,0,4,1;
        0.4,0,8,2;
        0.3,pi/2,4,2;
        0.3,pi/2,8,2;
        0.4,pi/2,4,1;
        0.4,pi/2,8,2;];
    gb = length(gbVec);
    sc = length(scVec);
    vec=[];
    nn=1;
    for i = 1:sc
        for cnl = 1:ncnls
            for sec = 1:secs
                filt = schmidFilter(scVec(i,1),scVec(i,2));
                pos = maxc(nn);
                neg = minc(nn);
                nn=nn+1;
                ss = (pos-neg)/bins;
                section = getSection(cnls(:,:,cnl),sec,secs);
                v = histcounts(imfilter(section, filt, 'symmetric'),(0:bins)*ss+neg);
                vec=cat(2,vec,v);
            end
        end
    end
    for i = 1:gb
        for cnl = 1:ncnls
            for sec = 1:secs
                filt = gaborFilter(gbVec(i,1),gbVec(i,2),gbVec(i,3),gbVec(i,4));
                pos = maxc(nn);
                neg = minc(nn);
                nn=nn+1;
                ss = (pos-neg)/bins;
                section = getSection(cnls(:,:,cnl),sec,secs);
                v = histcounts(imfilter(section, filt, 'symmetric'),(0:bins)*ss+neg);
                vec=cat(2,vec,v);
            end
        end
    end
end