scholarly journals CLASSIFICATION OF CROP-SHELTER COVERAGE BY RGB AERIAL IMAGES: A COMPENDIUM OF EXPERIENCES AND FINDINGS

2010 ◽  
Vol 41 (3) ◽  
pp. 1 ◽  
Author(s):  
Claudia Arcidiacono ◽  
Simona M.C.Porto
Keyword(s):  
Image Processing ◽  
Feature Recognition ◽  
Data Extraction ◽  
Object Oriented ◽  
Aerial Images ◽  
Basic Knowledge ◽  
Computational Time ◽  
Object Oriented Methods ◽  
Definition Of

Image processing is a powerful tool apt to perform selective data extraction from high-content images. In agricultural studies, image processing has been applied to different scopes, among them the classification of crop shelters has been recently considered especially in areas where there is a lack of public control in the building activity. The application of image processing to crop-shelter feature recognition make it possible to automatically produce thematic maps that constitute a basic knowledge for local authorities to cope with environmental problems and for technicians to be used in their planning activity. This paper reviews the authors’ experience in the definition of methodologies, based on the main image processing methods, for crop-shelter feature extraction from aerial digital images. Some experiences of pixel-based and object-oriented methods are described and discussed. The results show that the methodology based on object-oriented methods improves crop-shelter classification and reduces computational time, compared to pixel-based methodologies.

scholarly journals CLASSIFICATION OF TEXTURES WITH AND WITHOUT ROTATION ANGLES: A DAUBECHIES WAVELET BASED APPROACH

2014 ◽  
pp. 49-54
Author(s):  
SHAIKHJI ZAID M ◽  
J B JADHAV ◽  
V N KAPADIA
Keyword(s):  
Image Processing ◽  
Texture Classification ◽  
Daubechies Wavelet ◽  
Statistical Features ◽  
Visual Texture ◽  
Multi Resolution Analysis ◽  
Real Objects ◽  
Resolution Analysis ◽  
Definition Of

Textures play important roles in many image processing applications, since images of real objects often do not exhibit regions of uniform and smooth intensities, but variations of intensities with certain repeated structures or patterns, referred to as visual texture. The textural patterns or structures mainly result from the physical surface properties, such as roughness or oriented structured of a tactile quality. It is widely recognized that a visual texture, which can easily perceive, is very difficult to define. The difficulty results mainly from the fact that different people can define textures in applications dependent ways or with different perceptual motivations, and they are not generally agreed upon single definition of texture [1]. The development in multi-resolution analysis such as Gabor and wavelet transform help to overcome this difficulty. In this paper it describes that, texture classification using Wavelet Statistical Features (WSF), Wavelet Co-occurrence Features (WCF) and a combination of wavelet statistical features and co-occurrence features of wavelet transformed images with different feature databases can results better [2]. Several Image degrading parameters are introduced in the image to be classified for verifying the features. Wavelet based decomposing is used to classify the image with code prepared in MATLAB.

scholarly journals Image Processing in Artificial Intelligence

2020 ◽  
pp. 244-249
Author(s):  
Shahzeb Hussain ◽  
Prayas Dixit ◽  
Shaayan Hussain
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Data Extraction ◽  
Extraction Methods ◽  
Public Places ◽  
Ideal Object ◽  
Object Feature ◽  
Classical Image

Machines can learn to elucidate images the same way our brains do and analyse those images much more thoroughly than we can. When applied to Image Processing, Artificial Intelligence (AI) can propel face recognition and security functionality in public places, detecting and recognizing intruders, objects, and patterns in live images and videos, etc. Image processing technology focuses on the development of data extraction methods applied to the statistical classification of visual imagery. In classical image processing systems, an image is pre-processed to remove noise (denoising), segmented to produce close object boundaries, analysed to extract a representative feature, and compared to the ideal object feature vectors by a classifier to decide the nearest object classification and its associated level. In this paper, we discuss about digital image processing and the role of AI in it.

IMAGE ENGINEERING AND RELATED PUBLICATIONS

2002 ◽  
Vol 02 (03) ◽  
pp. 441-452 ◽  
Author(s):  
Y. J. ZHANG
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Image Understanding ◽  
New Classification ◽  
The Status ◽  
Definition Of ◽  
Statistical Survey

Image engineering is a discipline that includes image processing, image analysis, image understanding, and the applications of these techniques. To promote its development and evolvement, this paper provides a well-regulated explanation of the definition of image engineering, as well as its intention and extension. It also introduces a new classification of the theories of image engineering, and the applications of image technology. A thorough statistical survey on the publications in this discipline is carried out, and an analysis and discussion of the statistics from the classification results are presented. This work shows a general and an up-to-date picture of the status, progress, trends and application areas of image engineering.

scholarly journals Object-oriented methods of analyzing the parameters of interaction of speech and music language

2021 ◽  
pp. 29-40
Author(s):  
Elizaveta Stepanets
Keyword(s):  
Music Composition ◽  
Object Oriented ◽  
Broad Sense ◽  
Luciano Berio ◽  
Object Oriented Methods ◽  
Methodological Principles ◽  
The Moment ◽  
Analytical Approaches ◽  
New System

The article considers the methodological principles of analyzing the parameters of interaction of speech and music language in the context of object-oriented methods of Astafiev’s intonation theory, Yavorsky’s concept of music speech, the views on and ideas about the intonation basis of speech of Bonfeld, Medushevsky, Aranovsky and Nazaikinsky, and the new system of interaction of speech and music in the works of Helmut Lachenmann and  Luciano Berio. Music language and speech are the phenomena allowing for various intersections, complementarities and mutual interferences. These factors manifest themselves in various aspects spotlighting particular sides of these parameters characterizing speech and music language. Since there’s no unified methodology for analyzing these parameters at the moment, it is reasonable to study a music composition as a text (in a broad sense) using various methods of analysis. The author suggests considering the parameters of interaction of speech and music language in terms of object-oriented methods. In the works of composers, music and speech have different forms of interaction and, consequently, need to be studied via different analytical approaches. Comprehensive consideration of a piece of music as a text (by means of various approaches) allows considering it as an intercultural universum representing the code of the epoch. Based on the peculiarities of interpretation of voice as an instrument, and speech as music, and the opportunities it gives, the author formulates the classification of creative methods and principles and the system of analysis which can be used in musicology.   

Implementing collection classes with monads

1998 ◽  
Vol 8 (3) ◽  
pp. 231-276 ◽  
Author(s):  
ERNIE G. MANES
Keyword(s):  
Category Theory ◽  
Natural Transformation ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Formal Definition ◽  
Axiomatic Theory ◽  
Finite Set ◽  
Definition Of ◽  
The Relationship

In object-oriented programming, there are many notions of ‘collection with members in X’. This paper offers an axiomatic theory of collections based on monads in the category of sets and total functions. Heuristically, the axioms defining a collection monad state that each collection has a finite set of members of X, that pure 1-element collections exist and that a collection of collections flattens to a single collection whose members are the union of the members of the constituent collections. The relationship between monads and universal algebra leads to a formal definition of collection implementation in terms of tree-processing. Ideas from elementary category theory underly the classification of collections. For example, collections can be zipped if and only if the monad's endofunctor preserves pullbacks. Or, a collection can be uniquely specified by its shape and list of data if the morphisms of the Kleisli category of the monad are all deterministic, and the converse holds for commutative monads. Again, a collection monad is ordered if the monad's functor preserves equalizers of monomorphisms (so, in particular, if collections can be zipped the monad is ordered). Every implementable monad is ordered. It is shown using the well-ordering principle that a collection monad is ordered if and only if its functor admits an appropriated list-valued natural transformation that lists the members of each collection.

Development and Evaluation of Fuzzy Criteria for the Diagnosis of Rheumatoid Arthritis

1996 ◽  
Vol 35 (04/05) ◽  
pp. 334-342 ◽  
Author(s):  
K.-P. Adlassnig ◽  
G. Kolarz ◽  
H. Leitich
Keyword(s):  
Rheumatoid Arthritis ◽  
Reference Model ◽  
American Rheumatism Association ◽  
Uniform Definition ◽  
Sensitivity Rate ◽  
Fuzzy Techniques ◽  
Definition Of ◽  
Different Levels ◽  
Specificity Rate

Abstract:In 1987, the American Rheumatism Association issued a set of criteria for the classification of rheumatoid arthritis (RA) to provide a uniform definition of RA patients. Fuzzy set theory and fuzzy logic were used to transform this set of criteria into a diagnostic tool that offers diagnoses at different levels of confidence: a definite level, which was consistent with the original criteria definition, as well as several possible and superdefinite levels. Two fuzzy models and a reference model which provided results at a definite level only were applied to 292 clinical cases from a hospital for rheumatic diseases. At the definite level, all models yielded a sensitivity rate of 72.6% and a specificity rate of 87.0%. Sensitivity and specificity rates at the possible levels ranged from 73.3% to 85.6% and from 83.6% to 87.0%. At the superdefinite levels, sensitivity rates ranged from 39.0% to 63.7% and specificity rates from 90.4% to 95.2%. Fuzzy techniques were helpful to add flexibility to preexisting diagnostic criteria in order to obtain diagnoses at the desired level of confidence.

ABOUT THE PROBLEM OF CLASSIFICATION OF THE CONCEPTS OF INFORMATICS STUDIED AT SECONDARY SCHOOL

2018 ◽  
pp. 4-7
Author(s):  
S. I. Zenko
Keyword(s):  
Secondary School ◽  
Foreign Language ◽  
Computer Science ◽  
Parts Of Speech ◽  
The Third ◽  
The Cross ◽  
Definition Of

The article raises the problem of classification of the concepts of computer science and informatics studied at secondary school. The efficiency of creation of techniques of training of pupils in these concepts depends on its solution. The author proposes to consider classifications of the concepts of school informatics from four positions: on the cross-subject basis, the content lines of the educational subject "Informatics", the logical and structural interrelations and interactions of the studied concepts, the etymology of foreign-language and translated words in the definition of the concepts of informatics. As a result of the first classification general and special concepts are allocated; the second classification — inter-content and intra-content concepts; the third classification — stable (steady), expanding, key and auxiliary concepts; the fourth classification — concepts-nouns, conceptsverbs, concepts-adjectives and concepts — combinations of parts of speech.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

High-precision Classification of Small Insects with Similar Color and Shape Using Image Processing

2016 ◽  
Vol 136 (8) ◽  
pp. 1120-1127 ◽  
Author(s):  
Naoya Ikemoto ◽  
Kenji Terada ◽  
Yuta Takashina ◽  
Akio Nakano
Keyword(s):  
Image Processing ◽  
High Precision
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