diff --git a/videocr/video.py b/videocr/video.py
index a91fb80..7d29d58 100644
--- a/videocr/video.py
+++ b/videocr/video.py
@@ -4,13 +4,17 @@ import pytesseract
 import cv2
 import timeit
 
-from .models import PredictedFrame
+from .models import PredictedFrame, PredictedSubtitle
+
+
+SUBTITLE_BOUND = 10
 
 
 class Video:
     path: str
     lang: str
     num_frames: int
+    pred_frames: List[PredictedFrame]
 
     def __init__(self, path, lang):
         self.path = path
@@ -19,26 +23,58 @@ class Video:
         self.num_frames = int(v.get(cv2.CAP_PROP_FRAME_COUNT))
         v.release()
 
-    def _frame_ocr(self, img):
+    def _single_frame_ocr(self, img) -> str:
+        img = img[img.shape[0] // 2:, :]  # only use bottom half of the frame
         data = pytesseract.image_to_data(img, lang=self.lang)
         return data
 
-    def run_ocr(self):
+    def run_ocr(self) -> None:
         v = cv2.VideoCapture(self.path)
-        print(self.num_frames)
-        frames = (v.read()[1] for _ in range(40))
+        frames = (v.read()[1] for _ in range(self.num_frames))
 
+        # perform ocr to all frames in parallel
         with futures.ProcessPoolExecutor() as pool:
-            frames_ocr = pool.map(self._frame_ocr, frames, chunksize=1)
-            for i, data in enumerate(frames_ocr):
-                pred = PredictedFrame(i, data)
-                print(pred.text)
+            frames_ocr = pool.map(self._single_frame_ocr, frames, chunksize=10)
+            self.pred_frames = [PredictedFrame(i, data) 
+                                for i, data in enumerate(frames_ocr)]
 
         v.release()
 
+    def get_subtitles(self) -> str:
+        if self.pred_frames is None:
+            raise AttributeError(
+                'Please call self.run_ocr() first to generate ocr of frames')
+
+        # divide ocr of frames into subtitle paragraphs using sliding window
+        i = 0
+        j = 1
+        bound = SUBTITLE_BOUND
+        while j < self.num_frames:
+            fi, fj = self.pred_frames[i], self.pred_frames[j]
+
+            if fi.is_similar_to(fj):
+                bound = SUBTITLE_BOUND
+            elif bound > 0:
+                bound -= 1
+            else:
+                # divide subtitle paragraphs
+                para_new = j - SUBTITLE_BOUND
+                print(PredictedSubtitle(self.pred_frames[i:para_new]).text)
+                i = para_new
+                j = i
+                bound = SUBTITLE_BOUND
+
+            j += 1
+
+        if i < self.num_frames - 1:
+            print(PredictedSubtitle(self.pred_frames[i:]).text)
+
+        return ''
+
 
 time_start = timeit.default_timer()
 v = Video('1.mp4', 'HanS')
 v.run_ocr()
+v.get_subtitles()
 time_stop = timeit.default_timer()
 print(time_stop - time_start)