diff --git a/image_processing/processing/combination.py b/image_processing/processing/combination.py
index a75ecbd27..6b7778e63 100644
--- a/image_processing/processing/combination.py
+++ b/image_processing/processing/combination.py
@@ -3,15 +3,29 @@
 from skimage.exposure import match_histograms
 from skimage.metrics import structural_similarity
 
+# Função para encontrar a diferença entre duas imagens
 def find_difference(image1, image2):
-    assert image1.shape == image2.shape, "Specify 2 images with de same shape."
+    # Verifica se as duas imagens têm a mesma forma
+    assert image1.shape == image2.shape, "Specify 2 images with the same shape."
+    
+    # Converte as imagens para escala de cinza
     gray_image1 = rgb2gray(image1)
     gray_image2 = rgb2gray(image2)
+    
+    # Calcula a similaridade estrutural entre as duas imagens
     (score, difference_image) = structural_similarity(gray_image1, gray_image2, full=True)
     print("Similarity of the images:", score)
-    normalized_difference_image = (difference_image-np.min(difference_image))/(np.max(difference_image)-np.min(difference_image))
+    
+    # Normaliza a imagem de diferença para o intervalo [0, 1]
+    normalized_difference_image = (difference_image - np.min(difference_image)) / (np.max(difference_image) - np.min(difference_image))
+    
+    # Retorna a imagem de diferença normalizada
     return normalized_difference_image
 
+# Função para transferir o histograma de uma imagem para outra
 def transfer_histogram(image1, image2):
+    # Ajusta o histograma da primeira imagem para combinar com o da segunda
     matched_image = match_histograms(image1, image2, multichannel=True)
-    return matched_image
\ No newline at end of file
+    
+    # Retorna a imagem com o histograma ajustado
+    return matched_image