Application of mathematical morphology methods in terms of erosive processes research using aerial photography materials
dc.citation.epage | 83 | |
dc.citation.journalTitle | Геодезія, картографія і аерофотознімання : міжвідомчий науково-технічний збірник | |
dc.citation.spage | 76 | |
dc.citation.volume | 85 | |
dc.contributor.affiliation | Східноєвропейський національний університет імені Лесі Українки | |
dc.contributor.affiliation | Lesya Ukrainka Eastern European National University | |
dc.contributor.author | Мендель, В. | |
dc.contributor.author | Mendel, V. | |
dc.coverage.placename | Львів | |
dc.date.accessioned | 2018-09-24T12:03:36Z | |
dc.date.available | 2018-09-24T12:03:36Z | |
dc.date.created | 2017-03-28 | |
dc.date.issued | 2017-03-28 | |
dc.description.abstract | Встановлення планового розподілу ерозійних “плям” на сільськогосподарських землях на основі опрацювання бінарних зображень матеріалів аерофотознімання із застосуванням методів морфолого- планіметричного аналізу. Методика. Запропонована методика основується на застосуванні нелінійних операторів, які математично описуються теоретико-множинним формалізмом. Математична морфологія використовує два основних морфологічні фільтри, які можна представити як послідовні комбінації двох етапів аналізу зображення на основі використання базових морфологічних операторів: стиснення і розширення. Результати. Для отримання максимальних характеристик зображення запропоновано опрацювати в такій послідовності: бінаризація, сегментація та морфолого-планіметричні визначення. Зміст бінаризації полягає у тому, що світлі плями, які показують вихід грунтотвірних порід на поверхню можна відділити за відомим методом проф. В. М. Соколова з послідовним розбиттям пікселів. Такий процес є найвживанішим у цифровій фотограмметрії. Поданий відповідний математичний апарат. Наступним етапом опрацювання бінарного зображення було виділення суміжних границь та ділянок шляхом сегментації методом Лапласа. У такому разі оцінено дві різні контрастності областей А і В. Для встановлення границь їхнього поділу оцінюються знаки другої похідної перепаду контрастності. Запропоновано здійснювати сегментацію згідно з теорією графів. Ілюстрацію такої сегментації представлено графічно. На третьому етапі опрацювання проводяться морфолого-планіметричні визначення на досліджуваному зображені з використанням піксельних масок розміром 2×2. Як результат можна обчислити статистичні розподіли плям на аерофотознімках за площею, периметром та фактором форми. Наукова новизна. Запропонована методика поетапного опрацювання аерознімків основується на використанні методу бінаризації та сегментації, які дають змогу отримати чіткіше зображення, а відповідно і точніші результати морфолого-планіметричних визначень. Практична значущість. За запропонованим алгоритмом були проаналізовано деякі морфометричні характеристики плям на аерофотознімках: площа, периметр та фактор форми. Приклади застосування, що підтверджують універсальність запропонованого методу під час аналізу зображень у мікрофотограмметрії наведено у роботі [Мельник, 2013]. | |
dc.description.abstract | Planned distribution establishment of erosive “spots” of the agricultural lands is based on the processing of binary images of aerial photographic materials using morphological and planimetric methods of analysis. Methodology. Offered methodology is based on the non-linear operators’ application. These operators are mathematically described by the theoretical and set formalism. Mathematical morphology uses two main morphological filters which can be represented as a successive combination of two stages of image analysis on the basis of the morphological operators using: constriction and extending. Results. For obtaining maximal image characteristics it was suggested to carry out processing in the following sequence: binarization, segmentation, and morphological and planimetric definitions. Binarization content is characterized by bright spots, which show the release of soil-forming rocks to the surface, which can be divided by well-known method of prof. V. M. Sokolova (with sequential split pixels). The above-mentioned process is mostly used in digital photogrammetry. The corresponding mathematical apparatus is represented. The next stage of binary image processing is the allocation of adjacent boundaries and sites by the Laplace’s method of segmentation. In such a case, an estimation of two different contrast areas A and B is conducted. To determine the boundaries of their division, the marks of the contrast ratio’s second derivative are estimated. It is offered to carry out segmentation according to graph theory. An illustration of this segmentation is represented graphically. At the third stage of the study, morphological and planimetric determinations were performed on the investigated image using 2 × 2 pixel masks. As a result, it is possible to calculate statistical distributions of spots on aerial photographs by area, perimeter, and factor form. Scientific novelty. The offered method of step-by-step processing of aerial photography is based on the use of binary and segmentation methods which allow acquiring a precise image and more accurate results of morphological and planimetric definitions. Practical significance. According to the above-mentioned algorithm, some morphometric characteristics of spots on aerial photographs were analyzed: area, perimeter, and form factor. Application examples which confirm the universality of the suggested method for analyzing images in a microphotogrammetry are given in the work [Melnyk, 2013]. | |
dc.format.extent | 76-83 | |
dc.format.pages | 8 | |
dc.identifier.citation | Mendel V. Application of mathematical morphology methods in terms of erosive processes research using aerial photography materials / V. Mendel // Геодезія, картографія і аерофотознімання : міжвідомчий науково-технічний збірник. — Львів : Видавництво Львівської політехніки, 2017. — Том 85. — С. 76–83. | |
dc.identifier.citationen | Mendel V. Application of mathematical morphology methods in terms of erosive processes research using aerial photography materials / V. Mendel // Heodeziia, kartohrafiia i aerofotoznimannia : mizhvidomchyi naukovo-tekhnichnyi zbirnyk. — Lviv : Vydavnytstvo Lvivskoi politekhniky, 2017. — Vol 85. — P. 76–83. | |
dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/42798 | |
dc.language.iso | en | |
dc.publisher | Видавництво Львівської політехніки | |
dc.relation.ispartof | Геодезія, картографія і аерофотознімання : міжвідомчий науково-технічний збірник (85), 2017 | |
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dc.relation.referencesen | [Photogrammetry]. Lviv: Vydavnyctvo Nacional'nogo | |
dc.relation.referencesen | universytetu L'vivs'ka politehnika [Lviv | |
dc.relation.referencesen | Polytechnic Publishing House]. 2008, 332 p. | |
dc.relation.referencesen | Fowlkes C., Martin D., Malik J. Learning Affinity | |
dc.relation.referencesen | Functions for Image Segmentation: Combining | |
dc.relation.referencesen | Patch-based and Gradient-based Approaches. 2003. | |
dc.relation.referencesen | Kendall M., Moran P. Geometricheskie verojatnosti | |
dc.relation.referencesen | [Geometric Probabilities]. Moscow: Nauka | |
dc.relation.referencesen | [Science], 1972, 192 p. | |
dc.relation.referencesen | Kiberneticheskij sbornik. Novaja serija, issue. 27. Sb. | |
dc.relation.referencesen | statej: Per. s angl [Cybernetic collection. New | |
dc.relation.referencesen | series. 27. Sat. articles: Per. with English]. Moscow:Mir. 1990, 200 p. | |
dc.relation.referencesen | Marchukov V. S. Teorija i metody tematicheskoj | |
dc.relation.referencesen | obrabotki ajerokosmicheskih izobrazhenij na osnove | |
dc.relation.referencesen | mnogourovnevoj segmentacii [Theory and methods | |
dc.relation.referencesen | of thematic processing of aerospace images based on | |
dc.relation.referencesen | multilevel segmentation]. Avtoreferat dissertacii na | |
dc.relation.referencesen | soiskanie uchenoj stepeni doktora tehnicheskih nauk 25.00.34. Ajerokosmicheskie issledovanija zemli, | |
dc.relation.referencesen | fotogrammetrija [The dissertation author's abstract | |
dc.relation.referencesen | on the competition of a scientific degree of Doctor | |
dc.relation.referencesen | of Technical Sciences 25.00.34. Arospace studies of | |
dc.relation.referencesen | the earth, photogrammetric]. Moscow, MIIGAiK,2011. | |
dc.relation.referencesen | Melnyk V. M., Mendel V. P. Geometrychne doslidzhennja | |
dc.relation.referencesen | erozijnyh procesiv metodom trypletnoi' | |
dc.relation.referencesen | kvazikonvergentnoi' fototopografii [Geometrical | |
dc.relation.referencesen | study of erosive processes using the triplet quasiconvergent | |
dc.relation.referencesen | phototography technique]. Naukovyj visnyk | |
dc.relation.referencesen | Volyns'kogo nacional'nogo universytetu imeni Lesi | |
dc.relation.referencesen | Ukrai'nky [Scientific Bulletin of the Volyn National | |
dc.relation.referencesen | University named after Lesya Ukrainka]. 2012,no. 18(243), pp. 179–186. | |
dc.relation.referencesen | Melnyk V., Radzij V., Mendel V. Dejaki pytannja | |
dc.relation.referencesen | identyfikacii' modelej vodnoi' ta vitrovoi' erozii' | |
dc.relation.referencesen | [Some issues of identification of water and wind | |
dc.relation.referencesen | erosion models]. Suchasni dosjagnennja geodezychnoi' | |
dc.relation.referencesen | nauky ta vyrobnyctva [Modern achievements | |
dc.relation.referencesen | of geodesic science and production]. 2013,no. I (25), pp. 139–144. | |
dc.relation.referencesen | Melnyk V. M., Shostak A. V. Rastrovo-elektronna stereomikrofraktografija: | |
dc.relation.referencesen | monografija [Raster-electronic | |
dc.relation.referencesen | stereomicrofractography: monograph]. Luc'k: red.- | |
dc.relation.referencesen | vyd. vid. VNU im. Lesi Ukrai'nky [Lutsk: ed. from. | |
dc.relation.referencesen | VNU named after Lesia Ukrainka]. 2009, 468 p. | |
dc.relation.referencesen | Molchanova V. S. Adaptivnyj porogovyj metod binarizacii | |
dc.relation.referencesen | rastrovyh izobrazhenij tehnicheskih chertezhej | |
dc.relation.referencesen | [Adaptive threshold method of binarization of raster | |
dc.relation.referencesen | images of technical drawings]. Radioelektronika, | |
dc.relation.referencesen | informatika, upravlinnja [Radiation Electronics, | |
dc.relation.referencesen | Informatics, Management]. 2015, no. 2, pp. 62–70. | |
dc.relation.referencesen | Navon E., Miller O., Averbuch A. Color image segmentation | |
dc.relation.referencesen | based on adaptive local thresholds. Image | |
dc.relation.referencesen | and Vision Computing. 2012, no. 23, pp. 69–85. | |
dc.relation.referencesen | Pratikakis I., Gatos B., Ntirogiannis K. Document Image | |
dc.relation.referencesen | Binarization Contest (ICDAR 2013). ICDAR 2013:12th International Conference on Document | |
dc.relation.referencesen | Analysis and Recognition, USA, Washington, 25–28 | |
dc.relation.referencesen | August, 2013. Washington, 2013, pp. 1471–1476 | |
dc.relation.referencesen | Protsyk M. T. Metodi fotogrammetrichnogo ta | |
dc.relation.referencesen | kartografichnogo suprovodu bagatorivnevoi sistemi | |
dc.relation.referencesen | monitoringu erozijnih gruntovih procesiv: avtoref. | |
dc.relation.referencesen | disertacii kand. tehn. nauk [Methods of | |
dc.relation.referencesen | photogrammetric and cartographic support of a | |
dc.relation.referencesen | multilevel monitoring system for erosive soil | |
dc.relation.referencesen | processes: author's abstract. Theses Cand. tech | |
dc.relation.referencesen | Sciences]. Lviv, 2012, 26 p. | |
dc.relation.referencesen | Rozenfeld A. Raspoznavanie obrazov i obrabotka | |
dc.relation.referencesen | izobrazhenij [Image recognition and image | |
dc.relation.referencesen | processing]. Moscow: Mir, 1972, 230 p. | |
dc.relation.referencesen | Salnikov I. I. Metody raspoznavanija slozhnyh binarnyh | |
dc.relation.referencesen | izobrazhenij na osnove postrochnogo i sledjashhego | |
dc.relation.referencesen | analiza [Methods for recognizing complex binary | |
dc.relation.referencesen | images based on line and trace analysis]. | |
dc.relation.referencesen | "Iskusstvennyj intellekt" ["Artificial Intelligence"].2013, no. 3, pp. 242–252. | |
dc.relation.referencesen | Sauvola J., Pietikainen M. Adaptive Document Binarization. | |
dc.relation.referencesen | Pattern Recognition. 2000, no. 33, pp. 225–236. | |
dc.relation.referencesen | Sergeev V., Sokolov V. Quantitative morphological | |
dc.relation.referencesen | analysis in a SEM-microcomputer system. J. | |
dc.relation.referencesen | Quantitative shape analysis of sing fie objects. | |
dc.relation.referencesen | Journal of microscopy, 1984, V.135, Pt.1, pp. 1–12. | |
dc.relation.referencesen | Serra J. Image Analysis and Mathematical Morphology. | |
dc.relation.referencesen | London: Academic Press. 1992, pp. 329–341. | |
dc.relation.referencesen | Shostak A. V. Assessment of dispersed soils and their main | |
dc.relation.referencesen | rheological properties. Urban planning and territorial | |
dc.relation.referencesen | planning. Kyiv, 2011, issue 39, pp. 465–475. | |
dc.relation.referencesen | Sokolov V. N., Jurkovec D. I., Rozgulina O. V., Melnik | |
dc.relation.referencesen | V. N. Avtomatizirovannaja sistema morfologicheskogo | |
dc.relation.referencesen | analiza skeletnogo komponenta mikrostruktury | |
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dc.subject | аерофотознімки | |
dc.subject | сегментація | |
dc.subject | піксельна маска | |
dc.subject | бінаризація | |
dc.subject | ерозія | |
dc.subject | морфологічні фільтри | |
dc.subject | aerial photography | |
dc.subject | segmentation | |
dc.subject | pixel mask | |
dc.subject | binarization | |
dc.subject | erosion | |
dc.subject | morphological filters | |
dc.subject.udc | 528.854 | |
dc.title | Application of mathematical morphology methods in terms of erosive processes research using aerial photography materials | |
dc.title.alternative | Застосування методів математичної морфології під час дослідження ерозійних процесів за матеріалами аерофотозйомки | |
dc.type | Article |
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