Image Processing

1354 Words3 Pages

Abstract

This paper is about a selected few image processing applications. Optical Character Recognition is the translation of images of handwritten, typewritten or printed text into machine-editable text. Then I have introduced the captcha that we so frequently encounter in common websites. An algorithm trying to solve or break a captcha has been explained.

Face detection is a growing and an important tool in security these days. It must be applied before face recognition. There are many methods for recognizing faces and a few of them are discussed in the paper.

Contents

Topic Pg No

Image Processing

Optical character recognition

Captcha

Braking Captcha

Face Detection

Algorithm for Face Detection

References

Image processing

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.

Typical Operations

Among many other image processing operations are:

 Geometric transformation such as enlargement, reduction, and rotation

 Color corrections such as brightness and contrast adjustments, quantization, or conversion to a different color space

 Digital compositing or optical compositing (combination of two or more images).

 Interpolation, demosaicing, and recovery of a full image from a raw image format.

 Image editing (e.g., to increase the quality of a digital image)

 Image differencing (to determine changes between images)

 Image registration (alignment of two or more images)

 Image stabilization

 Image segmentation(partitioning a digital image into multiple regions)

 Extending dynamic range by combining differently exposed images

 2-D object recognition with affine invariance

Optical character recognition

Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic translation of images of handwritten, typewritten or printed text (usually captured by a scanner) into machine-editable text.

OCR is a field of research in pattern recognition, artificial intelligence and machine vision. Though academic research in the field continues, the focus on OCR has shifted to implementation of proven techniques. Optical character recognition (using optical techniques such as mirrors and lenses) and digital character recognition (using scanners and computer algorithms) were originally considered separate fields. Because very few applications survive that use true optical techniques, the OCR term has now been broadened to include digital image processing as well.

Early systems required training (the provision of known samples of each character) to read a specific font. "Intelligent" systems with a high degree of recognition accuracy for most fonts are now common.

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