1. (Project) by:- ROHAN 70229 HIMANSHU 70216 ANUP 70282
IMAGE PROCESSING
(Project) by:-
ROHAN
HIMANSHU
ANUP

2. INNOVATION PART
As the project demands for innovations & new ideas so there are three new things that we implemented in it : 1. Use of cryptography to encode a message 2. Edge detection. 3.Increase Brightness.

3. DIGITAL IMAGE
An image is a visual representation of an object or a person
Digital image is a discontinous image
It is made of small elements(PIXELS)
Represented(or stored) in form of binary numbers
A digital image is a rectangular array of pixels sometimes called a bitmap.

4. PIXELS (Picture Elements)
Each pixel represents the color (or gray level for black and white photos) at a single point in the image
arranged in rows and columns
The number of colours that a monitor can display, however, depends on how much memory is assigned to each pixel.

5. DIGITAL IMAGE REPRESENTATION
f (0, 0)
f (0, 1) ..
f (0,N − 1)
f (M − 1, 0)
f (M − 1,N − 1)
DIGITAL IMAGE REPRESENTATION

6. TYPES OF IMAGES
3 Types of images: Binary images (uses 1 bit per pixel, range 0 to 1 ) Gray level images (uses 8 bits per pixel, range 0 to 255) Color images (RGB Representation)
show in matlab

7. IMAGE PROCESSING TOOLBOX IN MATLAB
Image Processing Toolbox has many functions and Datatypes Uint8 - Range[0,255] Logical - Range[0 and 1] Double - Range[0,1] imshow[x,y] – shows a images with values less than x will be displayed as black and values more than y will be displayed as white Structures

8. imadd – combine two images imread – reads a picture image in form of matrix imsubtract - can be used to get negative images

9. Some Operation
Rotate image by 30 degree
Addition of two images

10. Colour image
An RGB color image in MATLAB corresponds to a 3D array of dimensions M × N × 3, where M and N are the image’s height
and width (respectively) and
3 is the number of color planes (channels).

11. IMAGE ENHANCEMENT Enhancement: to process an image so that the
result is more suitable than the original image
for a specific application.

12. Convolution
Convolution is a widely used mathematical operator that processes an image by computing—for each pixel—a weighted sum of values of that pixel and its neighbors.
It is used to detect or emphasize the high frequency and contents of an image, such as fine details, points, lines, and edges.

13. High pass Filter
High Pass filter technique works well at edge detection. The reason behind the edge detection is that edge always carry high frequency, so the high pass filter attenuates the low frequency and high frequency remains unchanged.

14. LOW PASS FILTER
Similarly, low pass filter works well for image sharpening

15. Maximizing Contrast
For each channel of the active layer, it finds the minimum and maximum values and uses them to stretch the Red, Green and Blue histograms to the full contrast range.
The bright colors become brighter and the dark colors become darker.

16. Cryptography
The area of cryptography employs many different means of transforming normal data into hard to read data.

17. Cryptography refers to encryption
[ which is the process of converting ordinary information into unintelligible gibberish ]
and
decryption
[which is the reverse, moving from the unintelligible cipher text back to plaintext ] .

18. Substitution cipher

19. Two major image operations
Image analysis : textual and numerical data extraction from an array of pixels representing image
Image synthesis : rendering an image from numerical data

20. Applying cryptography to image processing
A sender might start with any normal image file and adjust the colour of every 100th pixel to correspond to a letter in the message, a change so subtle that someone not specifically looking for it is unlikely to notice it.