this will introduce you about computer vision

1. Computer Vision
Presented by:- Kartik N. Kalpande

2. • Image Understanding
• Appeared in 1960s
• A sensor modality for robotics
• Computer emulation of human vision
• Inverse of Computer Graphics
Computer
vision
World
model
Computer
graphics
World
model

3.  Goal of computer vision is to write computer programs that
can interpret images.
 The image data can take many forms, such as a video
sequence, depth images, views from multiple cameras, or
multi-dimensional data from a medical scanner

4. What we see What a computer sees

5.  It is many-to-one mapping.
 It is computationally intensive.
 We do not understand the recognition problem.

7.  Image acquisition
 Pre-processing
 Feature extraction
 Detection/segmentation
 Recognition an interpretation

8.  Calculus
 Linear Algebra
 Probabilities and Statistics
 Signal processing
 Projective geometry
 Computational geometry
 OptimizationTheory
 ControlTheory

9.  Controlling processes
 Navigation
 Detecting events
 Organizing information
 Modeling objects or environments
 Interaction
 Automatic inspection

10. Identifying characters in images of printed or handwritten
text, usually with a view to encoding the text in a format
more amenable to editing or indexing
(eg. ASCII)

11. Identifying or verifying a person from a digital
image or a video frame from a video source.

12. Computing a 3D model of the
scene.

16. INDUSTRIAL ROBOTS MOBILE ROBOTS

17.  3D imaging
(MRI, CT)
 Image guided surgery

18.  Simpler and faster processes – fast computers replace
lengthy visual checks
 Reliability – cameras and computers, as opposed to a
human eye, never get tired. The human factor is
eliminated.
 Accuracy – your final products will be, thanks to
computer vision, flawless
 A wide range of use – ranging from banks to medical
care
 Cost reduction – you save time on people and devices,
faulty products are eliminated

19.  The field of computer vision has vastly
improved since it began in the 1960s.
Computers can now quickly and accurately
recognize thousands of faces, as well as a
growing number of other objects. Although
computer vision currently lacks the subtlety,
versatility, and general capabilities of human
vision, the gap is steadily closing.

20.  https//www.google.com
 https://wikipedia.org/wiki/computer_vision

21. Machines can’t replicate human image recognition.