Paper Info
Title
New Tools For Gray Level Histogram Analysis, Applications In Segmentation
Abstract
This paper summarizes three algorithms used for the analysis of gray level histograms. Two of them are developed generalizing standard techniques and the other is a completely new method. We will study the advantages of each and give examples of real-world use. Gray level histogram analysis (mainly threshold computation) is a known technique that allows easy and fast segmentation of the regions of interest in an image [1]. Many methods have been proposed for this problem [2], but almost all of them focus only on the problem of bimodal histograms. We will deal with multimodal histograms and, besides, we improve the time efficiency of the most widely used method (Otsu's [3]).
Year
DOI
Venue
2013
10.1007/978-3-642-39094-4_37
IMAGE ANALYSIS AND RECOGNITION
Keywords
Field
DocType
image analysis, gray level histograms, threshold computation, multimodal histogram, image segmentation
Computer vision,Histogram,Pattern recognition,Computer science,Segmentation,Generalization,Image segmentation,Artificial intelligence,Gray level,Computation
Conference
Volume
ISSN
Citations 
7950
0302-9743
0
PageRank 
References 
Authors
0.34
2
1
Name
Order
Citations
PageRank
Fernando Martín Rodríguez161.49