def text_extractor(self, image_obj):
temp_image_object = ImageObject()
self.__img_name = image_obj.get_image_name()
self.__height = image_obj.get_image_height()
self.__width = image_obj.get_image_width()
self.__img_matrix = image_obj.get_image_matrix()
left_limit = self.__width
right_limit = 0
top_limit = self.__height
bottom_limit = 0
for i in range(self.__width - 1):
for j in range(self.__height - 1):
variable = self.__img_matrix[j, i]
if self.__img_matrix[j, i] < 100:
if top_limit > j:
top_limit = j
if bottom_limit < j:
bottom_limit = j
a = self.__img_matrix[top_limit - 1:bottom_limit + 1, :]
temp_image_object.set_image_matrix(a)
temp_image_object.set_image_name('crop{}'.format(self.__img_name))
# self.i_writer.write_image(temp_object)
return temp_image_object
def split_image(self, image_object):
"""Splitting the image into letter wise images"""
# i_writer = ImageWriter()
# Extract all the parameters from the image object
self.__image_matrix = image_object.get_image_matrix()
self.__image_name = image_object.get_image_name()
self.__image_height = image_object.get_image_height()
self.__image_width = image_object.get_image_width()
has_black = False
pre_col_black = False
left_limit = 0
right_limit = 0
no = 0
for i in range(self.__image_width):
if has_black: # check previous column whether it has black
pre_col_black = True
has_black = False
for j in range(
self.__image_height): # Iterate row by row in each column
if self.__image_matrix[j, i] < 100:
has_black = True
if not pre_col_black:
left_limit = i
if pre_col_black and not has_black: # true when columns are black to white
no += 1
right_limit = i
image_width = right_limit - left_limit
char_img = self.__image_matrix[:,
left_limit - 1:right_limit + 1]
image_name = "{}char.bmp".format(no)
image_object = ImageObject()
image_object.set_image_matrix(char_img)
image_object.set_image_name(image_name)
image_object.set_image_width(image_width)
image_object.set_image_height(self.__image_height)
self.__image_list.append(image_object)
# i_writer.write_image(image_object)
pre_col_black = False
class Enhancement:
"""Pre-process of the Image"""
def __init__(self):
self.__grey_image = ImageObject()
self.__invert_grey_image = ImageObject()
self.__threshold_image = ImageObject()
self.__i_writer = ImageWriter()
# converting to gray is not needed since image is read in gray scale
def im_to_gray(self, image): # Create a grey image object
self.__grey_image.set_image_name("g{}".format(image.get_image_name()))
self.__i_writer.write_image(self.__grey_image)
def invert(self, image=ImageObject()):
"""Convert image into negative
@:parameter
imageObject
@:return
negative image object"""
self.__invert_grey_image.set_image_matrix(255 -
image.get_image_matrix())
self.__invert_grey_image.set_image_name("i{}".format(
image.get_image_name()))
self.__invert_grey_image.set_image_height(image.get_image_height())
self.__invert_grey_image.set_image_width(image.get_image_width())
self.__i_writer.write_image(self.__invert_grey_image)
return self.__invert_grey_image
def binarization(self, image=ImageObject()):
"""binarize the image using a threshold value
@:parameter
image object
@:return binarized image"""
image_val = image.get_image_matrix()
retval, img = cv2.threshold(image_val, 127, 255, cv2.THRESH_BINARY)
self.__threshold_image.set_image_matrix(img)
self.__threshold_image.set_image_name("binarized {}".format(
image.get_image_name()))
self.__threshold_image.set_image_height(image.get_image_height())
self.__threshold_image.set_image_width(image.get_image_width())
self.__i_writer.write_image(self.__threshold_image)
return self.__threshold_image