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With help from online article Python numpy array with multiple conditions to iterate over image

I was able to extract each BGR value then work on them to accomplish the same task on same image in around 4000 milliseconds

Here's the code

#Threshold
TOL = 90**2

#((c_r - ref_r).^2 + (c_g - ref_g).^2 + (c_b - ref_b).^2)
Res = (img[...,0]-[122])**2+(img[...,1]-[112])**2+(img[...,2]-[96])**2

#<= tolerance^2 then 255
Res[np.where(Res<=[TOL])]=[255]
Res[np.where(Res!=[255])]=[0]
Res1 = cv2.bitwise_not(Res.astype(np.uint8))
Res1 = cv2.merge((Res1,Res1,Res1))
Trest = cv2.bitwise_and(img,Res1)