Stiskanje rastrskih krivulj z algoritmom veriženja eksonov

magistrsko delo

David Podbregar (Author), David Podgorelec (Mentor)

Abstract

V magistrskem delu preučimo področje stiskanja rastrskih krivulj z verižnimi kodami. Pri algoritmih, ki ne kodirajo ločeno vsakega premika (piksla, simbola) vzdolž krivulje, ampak uvajajo samostojne kode tudi za pogostejša zaporedja dveh ali več premikov, se srečamo s problemom, ko je možno daljše zaporedje razdeliti na krajša podzaporedja na veliko različnih načinov. Za optimizacijo rešitve tega problema si sposodimo algoritem veriženja eksonov, ki v bioinformatiki služi za prepoznavanje (in primerjavo) neznanih genov. S pomočjo statističnih modelov ga prilagodimo za problem stiskanja rastrskih krivulj. V delu preučimo različne statistične modele in njihovo uspešnost pri stiskanju. S pomočjo programske implementacije predstavimo prednosti in slabosti razvitega pristopa. Na koncu nakažemo izhodišča za nadaljnje raziskave.

Keywords

verižna koda;rastrska krivulja;stiskanje podatkov;veriženje eksonov;Huffmanovo kodiranje;

Data

Language:	Slovenian
Year of publishing:	2013
Typology:	2.09 - Master's Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[D. Podbregar]
UDC:	004.627:004.925(043)
COBISS:	17105174
Views:	1700
Downloads:	99
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	RASTER CURVE COMPRESSION WITH EXON CHAINING ALGORITHM
Secondary abstract:	In this master’s thesis we study the field of raster curve compression with chain codes. In algorithms that don’t necessarily code every shift (pixel, symbol) of the curve but introduce separate codes for frequent sequences of two or more shifts, we meet with the problem when it’s possible to divide these longer sequences to shorter subsequences in many different ways. For optimizing this problem, we borrow exon chaining algorithm which in the field of bioinformatics serves for locating (and comparing) unknown genes. With the help of statistical models we adapt the algorithm for raster curve compression. In this work we study different statistical models and their successfulness at compression. With the help of implemented software we outline advantages and disadvantages of this approach. At the end, we point out results for further research.
Secondary keywords:	chain code;raster curve;data compression;exon chaining;Huffman coding;
URN:	URN:SI:UM:
Type (COBISS):	Master's thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko
Pages:	VIII, 51 f.
ID:	8726457