presentation on image processing ,created with purpose of helping engineering students.

2. Introduction

4. The general term “real time image processing"
refers to a computer discipline wherein digital
images are the main data object.
Real time image processing is continuous and
also called interactive processing.
It is having deadlines and predictable
response time with soft real-times, missing a
deadline indicates that the system is not working

5. This type of processing can be broken down into
several sub-categories, including: compression, image
enhancement, image filtering, image distortion, image
display and coloring.
Image processing is a physical process used to
convert aimage signal, either digital or analog, into a
physical image. The actual output itself can be an
actual physical image or the characteristics of an
image.
 The most common type is photography, in which an
image is captured using a camera to create a digital
or analog image. In order to produce a physical
picture, the image is processed using the appropriate
technology based on the input source type.

6. PIXEL NEIGHBOR
DIFFERENCES
EXAMPLES RELATED
TO IMAGE
PROCESSING
BRIGHTNESS
THRESHOLD

7. 2D IMAGE MAPPED TO 3D

8. The visual systems of humans and
higher animals exhibit a remarkable
ability to recognize seen objects robustly
and with high speed, tolerant of many
variances
In this project, a large hierarchical
neural network for object recognition was
designed and implemented on a
nueromorphic hardware system.

10. Image-to-image transformations
Image-to-information transformations
Information-to-image transformations
TYPES OF IMAGE PROCESSING

11. Enhancement (make image more useful,
pleasing)
Restoration
Egg. deblurring ,grid line removal
Geometry (scaling, sizing , Zooming,
Morphing one object to another).

12. Image statistics (histograms)
Histogram is the fundamental tool for
analysis and image processing
Image compression
Image analysis (image segmentation, feature
extraction, pattern recognition)
computer-aided detection and diagnosis
(CAD)

13. Decompression of compressed image data.
Reconstruction of image slices from CT or MRI raw
data.
Computer graphics, animations and virtual reality
(synthetic objects).

16. We are having an efficient tool that is ,named as
T-EXSPEED which is a powerful image processing software
that can detect other complex trajectory-based violations like
driving in the wrong direction, banned turning and
overtaking, insufficient distance between vehicles, etc.
Based on special video cameras, it does not require
additional sensors (inductive loops, radars or lasers). It is
available in both vehicle-mounted and tripod options or as a
stationary system.
The T-EXSPEED acquisition unit is equipped with two infrared,
sensitive and one-colour megapixel video cameras for vehicle 3D shape
reconstruction, speed measurement and license plate reading over two
lanes, in the same direction of travel or in the opposite direction. Its
infrared lighting system does not disturb drivers

17. SPEED CONTROLLERS

20. Video-based
interfaces for
human computer
interaction.

21.  The performance requirements of image processing
applications have continuously increased the computing
power of implementation platforms, especially when
they are executed under real time constraints.
 The real time applications may consist of different
image standards, or different algorithms used at
different stages of the processing chain.
 The computing paradigm using reconfigurable
architectures promises an intermediatetrade-off between
flexibility and performance.

22. 1. Customer can see the results immediately.
2. Allows you to automate your business.
This is especially important if your time is
very limited.
3. Real-time image processing also helps
eliminate customer errors.
4. Real-time image processing is fast .
5. Real-time image processing is continuous.

23. Causes many errors when many people code
together on the same document. There are chances
that they use the same variables for different
tasks.
In some cases infrared cameras used to detect the
object having low pixel capability. Therefore
object identification fails.

24. In electrical engineering and computer science,
image processing is any form of signal
processing for which the input is an image, such
as photographs or frames of video; the output of
image processing can be either an image or a set
of characteristics or parameters related to the
image. Most image-processing techniques involve
treating the image as a two-dimensional signal
and applying standard signal-processing
techniques to it.