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Pictorial Database Systems

Pictorial Database Systems. Faruk Kuşcan. Introduction. Pictures; Natural and effective objects to communicate for, People Computers Robotics. Introduction. Pictorial Information System; A new generation information system Capable of controlling and managing, Picture input device

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Pictorial Database Systems

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  1. Pictorial Database Systems Faruk Kuşcan

  2. Introduction • Pictures; • Natural and effective objects to communicate for, • People • Computers • Robotics

  3. Introduction • Pictorial Information System; • A new generation information system • Capable of controlling and managing, • Picture input device • Picture processor • Picture output device • Picture storage system • Picture communication interface • Pictorial Information System provides; • A collection of pictorial data for large amount of users

  4. Introduction Schematic Diagram of a Pictorial Information System

  5. Pictorial Database • Pictorial Database; • is the core of a pictorial information system • is a collection of sharable pictorial data encoded in various formats

  6. Pictorial Database • Previous Works • Algorithms for Finding Most Dissimilar Images • Algorithms for Finding Most Symmetric Images • Etc.

  7. Pictorial Database Until now, little attention has been paid to management of non-alphanumeric information such as digital pictures which requires a large amount of storage even for pictures of moderate complexity However, new applications which desire pictorial information handling are being created. Because of this increase, people started to work about pictorial database systems

  8. Pictorial Database • Pictorial information handling has been used in the following jobs; • Computer aided design • Robotics • Geographic data processing • Mapping applications • Remote sensing of earth resources • Medical data processing • Medical pictorial archiving • Etc.

  9. Pictorial Database Since, pictorial databases are being used in these kinds of jobs, problem of efficient and economic storage and flexible retrieval and manipulation of large amount of pictorial information has become more important.

  10. Pictorial Data Compressing Techniques Recently, some studies have been done about pictorial data compressing techniques with the increasing importance of pictorial databases used in a wide scale of applications.

  11. Pictorial Data Compressing Techniques The main idea in pictorial data compressing techniques is to reduce number of bits to transmit Because of the large amount of data even a small digital picture require, these techniques are important

  12. Pictorial Data Compressing Techniques • For binary pictures; • White block skipping coding technique • Run-length coding technique • A more efficient white block skipping coding method using a hierarchical block size

  13. White Block Skipping Coding Technique WBS is a method, that divides each scan line into N picture elements WBS uses “0” for all-white blocks WBS uses “1” for non-all-white block (at least it has one black in it) WBS compresses the image in this way with very small error

  14. Run Length Encoding • Run-Length encoding (RLE) is a very simple form of data compression in which “runs” of data are stored as a single data value and count, rather than as the original run. • Example (W: White, B: Black) • WWWWWWWWWWWWBWWWWWWWWWWWWBBBWWWWWWWWWWWWWWWWWWWWWWWWBWWWWWWWWWWWWWW • 12W1B12W3B24W1B14W

  15. Pictorial Data Compressing Techniques For grey pictures, run-length technique is used again. However, there must be another indicator before the data represents the level of grey.

  16. Pictorial Data Compressing Techniques For colored pictures, there are three values for each pixel. They are the values of red, green and blue. Just like binary pictures and grey pictures, if a single color exists n times repeatedly, run-length encoding technique can be used.

  17. Pictorial Data Compressing Techniques

  18. Pictorial Data Compressing Techniques In addition to run-length encoding technique, in colored pictures, there are some other techniques with some error. Some algorithms look for a pixel’s neighbours and makes a compression according to these data.

  19. Pictorial Data / Array Grammar • Array grammar is very powerful • Advantages are; • It is available to be multidimensional • It provides a sequential model • It can be highly parallel • Array grammar can be used to generate pictures

  20. Pictorial Data / Array Grammar • Array grammars are used as a pictorial data compressing tool • Array grammars are used to generate pictures

  21. Pictorial Data / Array Grammar The main idea in compressing pictures in array grammar is to find the suitable array grammar, which will be able to generate the initial picture when it is desired.

  22. Pictorial Data / Array Grammar • In addition to that; • The problem of array production minimization • Time and space complexity analysis • Pictorial knowledge • ER model These kind of things must be thought when compressing a picture as array grammar.

  23. Applying the ER Model to Picture Description There are primitive picture entities in the database. There are primitive descriptions. There are relations between these descriptions and picture entities.

  24. Extracting Pictorial Knowledge • Pictorial knowledge is divided into three classes • Angular pictorial knowledge • Side pictorial knowledge • Angular and side pictorial knowledge • Pictorial knowledge fields are, • “is a” • “has property” • “if and only if” fields with finite number of data like “0”,”1”,”true”,”false” etc.

  25. Extracting Pictorial Knowledge For example; triangular, quadrangular, and polygonal knowledge can be extracted from database.

  26. Extracting Pictorial Knowledge • Extracting pictorial knowledge from a database can be done in the following steps • Extracting pictorial knowledge from a picture • Extracting pictorial knowledge from a sequence of pictures • Extracting pictorial knowledge from a pictorial database

  27. PICQUERY A high level query language for pictorial databases Mostof the data management systems that have been implemented to manage pictorial information (digitizedimages, drawings, etc.) were developed for use inspecific application areas such as geographical applications,military reconnaissance, and medical applications. Very few generalized systems have been developed. Consequentlythe access or query languages developed forthese systems are also largely application specific.

  28. PICQUERY A basic command with picquery< Command Name >( < set of variable type statements > )<set of data base assignment statements>,FOR < set of data base grid cells > ;

  29. PICQUERY • Basic commands are; • COMPUTE • LIST • DISTANCE • ADD • REPLACE • DELETE • PRINT

  30. Image Manipulation Operations in PICQUERY • Panning or shifting operation to view different sectionsof an image • Rotation of images to give a different view of theimage • Zooming operations • Vertical Zooming • Horizontal Zooming • Diagonal Zooming • Superimposing of one picture over another (something like pictorial join) • Color transformation, to display a picture using differentcolor combinations • Projection operation on an image

  31. Pattern Recognition Operations in PICQUERY Edge detection, to detect edges by measuringchanges in light intensity along the picture Thresholding, to build a binary image which is whitein the regions with light intensity less than a thresholdlimit and black elsewhere Similarity retrieval (or template matching) to identifyor retrieve picture objects which are similar to a givenpicture using a certain similarity measure or which matchcertain template patterns. Similarity retrieval can be doneon the basis of size, shape, texture, etc.

  32. Spatial or Geometric Operations in PICQUERY Distance operation (point to point, point to line,point to region, line to line, line to region, region to region) Length, center, slope of a line Area, centroid, perimeter of a region Operation to find the portion of a given line object Operation to find the portion of a given region object Intersection of a point and a line Union of two region objects. Difference between two region objects.

  33. PICQUERY Syntax

  34. Conclusion Pictorial databases are being used recently There is an increase in the number of applications which use pictorial databases Because of these increase, there are some studies about pictorial databases Operations in pictorial databases time and space complexities are high, so there are some compressing and extracting techniques to reduce the number of bits transmitted

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