Detect handwritten characters bounded by a box with OpenCV - opencv

Question

I am trying to read a handwritten form which has boxed-input.
I have run tesseract on the image but get strange results. In my understanding, I suppose the best thing to do is to detect the bounding box and minus that from the image. What's the best way to detect the box (semi-box around the character). I tried cv2.HoughLines(), but with no result.
I am new to OpenCV. It will be really helpful if someone can help me out here.

Answer 1

Thanks for your idea. I just realized probably i can look at counting the vertical pixels and greater than certain threshold
def get_pixel_count_in_col(img,col):
count=0
for j in range(img.shape[0]):
if(img[j,col]<255):
count=count+1
return count
def cleanup_img(img):
foundlines=[]
for i in range(img.shape[1]):
if(get_pixel_count_in_col(img,i)>img.shape[0]*0.7):
foundlines.append(i)
if(get_pixel_count_in_col(img,i-1)>img.shape[0]*0.25):
foundlines.append(i-1)
if(get_pixel_count_in_col(img,i+1)>img.shape[0]*0.25):
foundlines.append(i+1)
return np.delete(img,foundlines,1)
The resulting image makes more sense. But is there any other easy way to do this ?

Answer 2

It seems that your input format is quite clean and consistent. You can simply hard-code the width of each box in pixels and crop out the characters. However if the input format is not fixed then we can extend this answer to handle that as well(it would be bit expensive), so as the first attempt we would simply go with hard coding the width of boxes in pixels.
def get_image_chunks(img, size):
chunks = []
# To remove black borders
padding = 2
for i in xrange(0, img.shape[1], size):
col_start = i + padding
col_end = i + size - padding
# Slicing the numpy array.
chunks.append(img[:-padding, col_start:col_end])
return chunks
img = cv2.imread("/Users/anmoluppal/Downloads/GLUmJ.jpg", 0)
chunks = get_image_chunks(img, 42)
Outputs:
;
;