Image to Text Converter PPT. PPT contains step by step algorithms/methods to which we can convert images in to text , specially contains algorithms for images which contains human handwritting, can convert writting in to text, img to text.

1. Image to Text Convertor
BY,
DHIRAJ RAJ
MANVENDRA PRIYADARSHI

2. Agenda :
 Abstract
 AIM
 Technology Used
 Procedure
 Algo I
 Algo II
 Algo III
 Algo IV (Part 1 & 2)
 Algo V (Part 1 & 2)
 Advantage
 Limitations
 Conclusion

3. Abstract :
 Image to text converter is a type of application that can be used to translate images of any format to the
text format. This application helps one to convert the texts in image files into editable text files.
 It has some pre-requisite conditions saying first that the text captured should be aligned horizontally
straight. Then the text in the image to be converted contains only A, B, C, and D of pre-defined fonts or
human written fonts. The image should be captured in a way that the pixel of any of the text should not be
present at the coordinate (0, 0). And also the image captured should have texts with intensity of dark color
and the background with intensity of light color.
 This program basically uses five specific algorithms where the first algorithm deals with converting the text
pixels and the background pixels other than text into opposite ranges of RGB so that the text pixels could
be identified with ease.
 In the second algorithm the image obtained previously is horizontally searched for all the portion of text (in
black) area and the dimension of each sentence is found. An array of BufferedImage type is used to store
the separated images containing each sentence. The dimension for the portion of image is defined to that
array, which is separated by using predefined method drawImage().
 The third algorithm deals with extracting each word from each of these sentences into specific images. The
words are separated using drawImage() and stored in an array of BufferedImage type.

4. Abstract Contd.
 The forth algorithm has two parts. The first part deals with extracting each letters from each of the
words which contain letters of predefined uppercase texts format and the second part deals with
extracting each of the letters from each of the words which contain letters of joint lowercase texts
format.
 The last algorithm deals with extracting each letters from each the words and convert each letter into
specific images. The obtained image of letter is then converted into a size with 100x100 pixels using
predefined method drawImage() for changing the pixels of the image. The image is matched with
predefined strips of co-ordinate. If the image matches every strips condition for letters (particularly
for A, B, C & D) then it gets validated for that letter. And, we display the corresponding letter as an
output.

5. Aim :
 To build an application to covert in to editable text from image(with
standard text/human handwritting).

6. Technology Used :
 Language : Java
 IDE : NetBeans

7. Procedure :
 Step 1 : Firstly, we have change the color of background to be white and
the color of text to be black.
 Step 2 : Now, we separate every sentence from the given segment.
 Step 3 : Then, we split each sentence into words.
 Step 4 : Each word will then split into letters.
 Step 5 : Now, we convert the obtained letter into 100x100 pixels.
 Step 6 : Then, we match the letter with predefined strips of co-ordinate
and validate the letter to be specified one.
 Step 7 : Finally, we display the corresponding letter as an output.

8. Algo I :
 To change the color of image, we have used predefined class ‘Color’ which
is available in java.awt package.
 Color c1 = new Color(255, 255, 255); // for White
 Color c2 = new Color(0, 0, 0); // for Black
Input : Output :

9. Algo II :
 Now, we separate each sentence from the given segment.
 We start searching horizontally, all the portion of text (in black) area and
count it separately for every horizontal line and store it into an array.
 Then we look for that line which has white portion and the previous line
should have some text portion and store the co-ordinate of that line into
an array.
 Then we also look for that line which has white portion and the next line
should have some text portion and store the co-ordinate of that line into
the same array.
 Now, we have the co-ordinates of image from which we need to separate
the image.

10. Algo II continues….
 We have created an array of BufferedImage type to store the separated images.
 BufferedImage imgs[ ] = new BufferedImage[size];
 Then we defined the dimension for the portion of image to that array, which is need to
be separated.
 We used predefined method drawImage() for separating the image.
Output :Input :

11. Algo III :
 Now, we split each word from the sentence.
 We start searching vertically, all the portion of text (in black) area and count it
separately for every vertical line and store it into an array.
 Then we look for that line which has white portion and the increment the
counter by one until we find a line which has text portion onto it and store
value of counter into an array and the co-ordinate of that line into another
array and use ‘continue’ keyword to skip that iteration and execute next
iteration. Also, assign zero to counter so that it calculate next gap.
 Then we find the maximum value from the counter and store the co-ordinate
of the corresponding line into an array .
 Now, we have the co-ordinates of image from which we need to separate the
image.

12. Algo III continues….
 Again, we have created an array of BufferedImage type to store the separated images.
 BufferedImage imgs[ ] = new BufferedImage[size];
 Then we defined the dimension for the portion of image to that array, which is need to
be separated.
 We used predefined method drawImage() for separating the image.
Input : Output :

13. Algo IV (Part 1 : Font Text)
 Now, we split each letter (font text) from the word.
 We start searching vertically, all the portion of text (in black) area and
count it separately for every vertical line and store it into an array.
 Then we look for that line which has white portion and the previous line
should have some text portion and we shift the value to adjust the gap
then store the co-ordinate of that line into an array.
 Now, we have the co-ordinates of image from which we need to separate
the image.

14. Algo IV (Part 1 : Font Text) continues….
 Again, we have created an array of BufferedImage type to store the separated images.
 BufferedImage imgs[ ] = new BufferedImage[size];
 Then we defined the dimension for the portion of image to that array, which is need to
be separated.
 We used predefined method drawImage() for separating the image.
Input : Output :

15. Algo IV (Part 2 : Hand written Text)
 Now, we split each letter (hand written text) from the word.
 We start searching vertically, all the portion of text (in black) area and
count it separately for every vertical line and store it into an array.
 Then we look for that line which has minimum portion of text and store
the co-ordinate of that line into an array.
 We find the line which is next to the stored co-ordinate of minimum
portion of text and if it is more than all the minimum portions stored in the
array then we shift the value to adjust the gap then store the co-ordinate
of that line into another array.
 Now, we have the co-ordinates of image from which we need to separate
the image.

16. Algo IV (Part 2 : Hand written Text)
continues….
 Again, we have created an array of BufferedImage type to store the separated images.
 BufferedImage imgs[ ] = new BufferedImage[size];
 Then we defined the dimension for the portion of image to that array, which is need to
be separated.
 We used predefined method drawImage() for separating the image.
Input : Output :

17. Algo V (Part 1) :
 We convert the obtained image of letter into 100x100 pixels.
 For this purpose we convert the size of image into 100x100 pixels.
 We used predefined method drawImage() for changing the pixels of the
image.
Input : Output :

18. Algo V (Part 2) :
 We have defined some strips condition for letters (particularly for A, B, C &
D).
 We match the image with predefined strips of co-ordinate.
 If the image matches every strips condition then it get validated for that
letter.
 And, we display the corresponding letter as an output.
Input : Output :
ABCD

19. Advantage :
 Image to text converter utility helps in format portability and compatibility
that serves the purpose of using conversion from one format to another. In
the present scenario, interchangeable formats are more in demand and
software developers around the world need utilities that can convert files
from one format to another easily and without too much hassle. This is
where the ‘Image To Text Converter’ utility comes into play and the
benefits of using the same are required. Further, many of the media
houses use the converted files to store and retrieve data whenever they
need. This helps in files restoring of image files at one's convenience
making life easier for everyone in the process.

20. Limitations :
 The first co-ordinate (0,0) of the image should not be the portion of text.
 The handwritten text extracting process is successful for few letters yet.
 The joining portion of the hand written text should not have more
thickness.

21. Conclusion :
 By this project we can come to the conclusion that we can convert image’s texts into
editable text.

22. References :
 http://alvinalexander.com/blog/post/java/getting-rgb-values-for-each-pixel-in-image-
using-java-bufferedi
 http://alvinalexander.com/java/java-image-how-to-crop-image-in-java
 http://kalanir.blogspot.in/2010/02/how-to-split-image-into-chunks-java.html
 http://www.codejava.net/java-se/graphics/how-to-resize-images-in-java

23. Thank You