dor_id: 4110118

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590.#.#.d: Los artículos enviados a la revista "Journal of Applied Research and Technology", se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Scopus, Directory of Open Access Journals (DOAJ); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Indice de Revistas Latinoamericanas en Ciencias (Periódica); La Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc); Consejo Nacional de Ciencia y Tecnología (CONACyT); Google Scholar Citation

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336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://jart.icat.unam.mx/index.php/jart

351.#.#.b: Journal of Applied Research and Technology

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

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850.#.#.a: Universidad Nacional Autónoma de México

856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/656/639

100.1.#.a: Shabat, Abuobayda M.; Tapamo, Jules Raymond

524.#.#.a: Shabat, Abuobayda M., et al. (2017). A comparative study of the use of local directional pattern for texture-based informal settlement classification. Journal of Applied Research and Technology; Vol. 15 Núm. 3. Recuperado de https://repositorio.unam.mx/contenidos/4110118

245.1.0.a: A comparative study of the use of local directional pattern for texture-based informal settlement classification

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2017

264.#.1.c: 2019-06-07

653.#.#.a: Informal settlements; Texture features; Gray level co-occurrence matrix; Local directional pattern; Classification

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx

884.#.#.k: https://jart.icat.unam.mx/index.php/jart/article/view/656

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041.#.7.h: eng

520.3.#.a: In developing and emerging countries progression of informal settlements has been a fast growing phenomenon since the mid-1990s. Half of the world’s population is housed in urban settlements. For instance, the growth of informal settlements in South Africa has amplified after the end of apartheid. In order to transform informal settlements to improve the living conditions in these areas, a lot of spatial information is required. There are many traditional methods used to collect these data, such as statistical analysis and fieldwork; but these methods are limited to capture urban processes, particularly informal settlements are very dynamic in nature with respect to time and space. Remote sensing has been proven to provide more efficient techniques to study and monitor spatial patterns of settlements structures with high spatial resolution. Recently, a new feature method, local directional pattern (LDP), based on kirsch masks, has been proposed and widely used in biometrics feature extraction. In this study, we investigate the use of LDP for the classification of informal settlements. Performance of LDP in characterizing informal settlements is then evaluated and compared to the popular gray level co-occurrence matrix (GLCM) using four classifiers (Naive-Bayes, Multilayer perceptron, Support Vector Machines, k-nearest Neighbor). The experimental results show that LDP outperforms GLCM in classifying informal settlements.

773.1.#.t: Journal of Applied Research and Technology; Vol. 15 Núm. 3

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

310.#.#.a: Bimestral

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.1016/j.jart.2016.12.009

harvesting_date: 2023-11-08 13:10:00.0

856.#.0.q: application/pdf

file_creation_date: 2017-06-19 21:50:01.0

file_modification_date: 2017-06-19 17:19:52.0

file_creator: Abuobayda M. Shabat

file_name: 1509cbab76c91de882bcf93d5674970a0246c5ad776bdc62a826226a97827ac2.pdf

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last_modified: 2024-03-19 14:00:00

license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es

license_type: by-nc-sa

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Artículo

A comparative study of the use of local directional pattern for texture-based informal settlement classification

Shabat, Abuobayda M.; Tapamo, Jules Raymond

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Shabat, Abuobayda M., et al. (2017). A comparative study of the use of local directional pattern for texture-based informal settlement classification. Journal of Applied Research and Technology; Vol. 15 Núm. 3. Recuperado de https://repositorio.unam.mx/contenidos/4110118

Descripción del recurso

Autor(es)
Shabat, Abuobayda M.; Tapamo, Jules Raymond
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
A comparative study of the use of local directional pattern for texture-based informal settlement classification
Fecha
2019-06-07
Resumen
In developing and emerging countries progression of informal settlements has been a fast growing phenomenon since the mid-1990s. Half of the world’s population is housed in urban settlements. For instance, the growth of informal settlements in South Africa has amplified after the end of apartheid. In order to transform informal settlements to improve the living conditions in these areas, a lot of spatial information is required. There are many traditional methods used to collect these data, such as statistical analysis and fieldwork; but these methods are limited to capture urban processes, particularly informal settlements are very dynamic in nature with respect to time and space. Remote sensing has been proven to provide more efficient techniques to study and monitor spatial patterns of settlements structures with high spatial resolution. Recently, a new feature method, local directional pattern (LDP), based on kirsch masks, has been proposed and widely used in biometrics feature extraction. In this study, we investigate the use of LDP for the classification of informal settlements. Performance of LDP in characterizing informal settlements is then evaluated and compared to the popular gray level co-occurrence matrix (GLCM) using four classifiers (Naive-Bayes, Multilayer perceptron, Support Vector Machines, k-nearest Neighbor). The experimental results show that LDP outperforms GLCM in classifying informal settlements.
Tema
Informal settlements; Texture features; Gray level co-occurrence matrix; Local directional pattern; Classification
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

Enlaces