Name: Design Software for Classify Objects for Air Photos & Satellite Images (en Inglés)
Price: 247.01 PEN
Availability: InStock
Author: Samaher Hussein Ali
ISBN: 9783659449192

portada Design Software for Classify Objects for Air Photos & Satellite Images (en Inglés)

Formato

Libro Físico

Autor

Samaher Hussein Ali

Editorial

LAP Lambert Academic Publishing

Idioma

Inglés

N° páginas

160

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 0.9 cm

Peso

0.24 kg.

ISBN13

9783659449192

Categorías

Software empresarial

Design Software for Classify Objects for Air Photos & Satellite Images (en Inglés)

Samaher Hussein Ali (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

Libro Nuevo

S/ 247,01

S/ 494,02

Ahorras: S/ 247,01

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Origen: España (Costos de importación incluídos en el precio)

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Reseña del libro "Design Software for Classify Objects for Air Photos & Satellite Images (en Inglés)"

This Book presents a method to design programming system using hybrid techniques represented soft computing to classify objects from the air photos and satellite images depending on their features with minimum acceptable error.This book concerns with classifying five kinds of objects (urban area, forests, roads, rivers and football-stadiums). Accordingly, the database which describes that objects by depending on their attributes were built.Then, the breeder genetic algorithm to procedure genetic clustering process to segment image which provides a number of clusters found in that image data set were used.To avoid the overlapping between clusters with other, one of the clustering validity measures called "Davies-Bouldin index"as fitness function and four type of Crossover are used. Then, two types of features for each cluster which are visual features including (Pattern, Shape, Texture, Shadow, Associative), and statistical features represented by spectrum features that include(Intensity, Hue, Saturation) were extracted. After that, feed forward neural network from type error back propagation neural network to determine the class under which each feature vector belongs to was used.