diff --git a/helpers/images.py b/helpers/images.py
new file mode 100644
index 00000000..e69de29b
diff --git a/helpers/ocr.py b/helpers/ocr.py
new file mode 100644
index 00000000..622334e1
--- /dev/null
+++ b/helpers/ocr.py
@@ -0,0 +1,133 @@
+
+from PIL import Image
+import pytesseract
+import argparse
+import cv2
+import os
+import glob
+
+def ocr_file(filename):
+    # load the example image and convert it to grayscale
+    image = cv2.imread(filename)
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    # check to see if we should apply thresholding to preprocess the
+    # image
+
+    text = pytesseract.image_to_string(Image.open(filename))
+
+    gray_mask = cv2.threshold(gray, 220, 255,
+            cv2.THRESH_BINARY)[1]
+
+    temp_file = "{}.png".format(os.getpid())
+    cv2.imwrite(temp_file, gray_mask)
+
+    # load the image as a PIL/Pillow image, apply OCR, and then delete
+    # the temporary file
+    text = text + pytesseract.image_to_string(Image.open(temp_file))
+    os.remove(temp_file)
+    #print(text)
+    return text
+
+# show the output images
+#cv2.imshow("Image", image)
+#cv2.imshow("Output", gray)
+#cv2.waitKey(0)
+
+def check_text(text):
+    text = text.lower()
+    strings = ("REF", "RK9", "RBZ", "RA9", "RH8", "Accession", "patient", "nhs")
+    if any(s.lower() in text for s in strings):
+        return True
+
+def search_image(file_name):
+    print("Process: {}".format(file_name))
+    img = cv2.imread(file_name)
+
+    img_final = cv2.imread(file_name)
+    img2gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    ret, mask = cv2.threshold(img2gray, 240, 255, cv2.THRESH_BINARY)
+
+    #cv2.imshow("mask", mask)
+    
+    image_final = cv2.bitwise_and(img2gray, img2gray, mask=mask)
+    #ret, new_img = cv2.threshold(image_final, 180, 255, cv2.THRESH_BINARY)  # for black text , cv.THRESH_BINARY_INV
+    '''
+            line  8 to 12  : Remove noisy portion 
+    '''
+    kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (3,
+                                                         3))  # to manipulate the orientation of dilution , large x means horizonatally dilating  more, large y means vertically dilating more
+    dilated = cv2.dilate(image_final, kernel, iterations=9)  # dilate , more the iteration more the dilation
+
+    # for cv2.x.x
+
+    #_, contours, hierarchy = cv2.findContours(dilated, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)  # findContours returns 3 variables for getting contours
+
+    # for cv3.x.x comment above line and uncomment line below
+
+    contours, hierarchy = cv2.findContours(dilated,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
+
+
+
+    for contour in contours:
+        # get rectangle bounding contour
+        [x, y, w, h] = cv2.boundingRect(contour)
+
+        # Don't plot small false positives that aren't text
+        if w < 35 and h < 35:
+            continue
+
+
+        #you can crop image and send to OCR  , false detected will return no text :)
+        cropped = image_final[y :y +  h , x : x + w]
+
+        s = 'temp.png' 
+        cv2.imwrite(s , cropped)
+        text = ocr_file(s)
+        os.remove(s)
+
+        #cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
+
+        if check_text(text):
+            # draw rectangle around contour on original image
+            cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 0), -1)
+
+            path, fn = file_name.rsplit("/", 1)
+
+            edit_path = "{}/test/".format(path)
+
+            print(edit_path)
+            fn1, fn2 = fn.rsplit(".", 1)
+            cv2.imwrite("{}{}_new.{}".format(edit_path, fn1, fn2), img)
+
+            old_img = cv2.imread(file_name)
+            cv2.imwrite("{}{}".format(edit_path, fn), old_img)
+
+
+    # write original image with added contours to disk
+    #cv2.imshow('captcha_result', img)
+    #cv2.waitKey()
+
+
+
+#file_name = 'ankle4.jpg'
+#captch_ex(file_name)
+#
+#file_name = 'ankle1_n2mBhsm.jpg'
+#captch_ex(file_name)
+#ocr_file("ankle4.jpg")
+
+# file_name = 'chest_UUSUv8E.jpg'
+# captch_ex(file_name)
+#file_name = 'l1_DvMrQpv.jpg'
+#captch_ex(file_name)
+#file_name = 'renalmets_ct.jpg'
+#captch_ex(file_name)
+image_list = []
+
+file_types = ("gif", "jpg", "jpeg", "png")
+for file_type in file_types:
+    for filename in glob.glob('/Users/ross/media/test/*.{}'.format(file_type)): #assuming gif
+        image_list.append(filename)
+
+for f in image_list:
+    search_image(f)
diff --git a/requirements.txt b/requirements.txt
index 849d1206..733a804c 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -11,4 +11,6 @@ django-tables2
 django-filter
 django-filer
 psycopg2-binary
-django-sortedm2m
\ No newline at end of file
+django-sortedm2m
+pytesseract
+opencv-python
\ No newline at end of file