Automatic Building Extraction and Regularization from Image Matching Based Point Cloud

Year 2022, Volume: 4 Issue: 1, 25 - 35, 15.06.2022

Buray Karslı , Ferruh Yılmaztürk

https://doi.org/10.51489/tuzal.1098240

Abstract

Manually determining building layer boundaries with classical or remote sensing data is a time-consuming and effort-intensive process. Point clouds produced by matching from images contain dense and high-accuracy 3D information. Automatic extraction of buildings from 3D point clouds is a difficult problem in terms of geometric irregularities and the density and precision of the point cloud. In this study, the improved Octree (I-Octree) approach was developed by automating the voxel-based octree method, and automatic extraction and regularization of building details on point clouds produced from images are aimed. Point clouds were produced in study area (Elazig region), ground and above ground objects were sorted by SMRF, building objects are classified by removing noise with DBSCAN algorithm, and Octree and I-Octree methods were applied to the classified objects, then the edges of the building details are smoothed with the ABORE method. Automatically extracted building data were validated with pixel-based completeness, accuracy, quality, and F-score metrics with the support of reference map containing the study area. Validation results were obtained for each metric above 94%. It was concluded that the I-Octree approach developed can contribute to a fast and inexpensive map production process at the point of extracting the building details.

Keywords

Photogrammetry, point cloud, building extraction, I-Octree, digitalization

Görüntü Eşleştirme Kaynaklı Nokta Bulutu Üzerinden Otomatik Bina Çıkarımı ve Düzgünleştirme

Abstract

Harita bileşeni bina katmanı sınırlarının klasik veya uzaktan algılama verilerinden manuel olarak belirlenmesi zaman alıcı ve çaba gerektiren önemli bir işlemdir. Görüntülerden eşleştirme yöntemiyle üretilen nokta bulutları, yoğun ve doğruluğu yüksek üç boyutlu (3B) konum bilgisi içermektedir. Binaların 3B nokta bulutlarından otomatik olarak çıkarılması geometrik düzensizlikleri, çıkarılacakları nokta bulutu yoğunluğu ve hassasiyeti açısından zor bir problemdir. Bu çalışmada, voksel temelli sekizdal (Octree) veri organizasyon metodu otomatikleştirilerek iyileştirilmiş Octree (I-Octree) yaklaşımı geliştirilmiş ve görüntülerden üretilen nokta bulutları üzerinde bina detaylarının otomatik çıkarımı ve düzgünleştirilmesi amaçlanmıştır. Elazığ bölgesinde seçilen çalışma alanında 3B nokta bulutu görüntülerden üretilmiş, zemin ve zemin üstü objeler SMRF metodu ile ayıklanmış, DBSCAN algoritması ile bina objeleri gürültülerden ayıklanarak sınıflandırılmış ve sekizdal ile I-Octree yöntemlerinin sınıflandırılan objelere uygulanması ile ortaya çıkarılan bina detaylarına ABORE metodu ile kenar düzgünleştirmesi işlemi uygulanmıştır. Otomatik olarak çıkarılan bina verileri çalışma alanını içeren 1/1000 ölçekli hâlihazır harita referans verisi desteğiyle piksel tabanlı tamlık (Cp), doğruluk (Cr), kalite (Q) ve F-skor (F-1) metrikleri ile doğrulanmıştır. Doğrulama sonuçları her bir metrik için maksimum değer olarak %94 üzerinde elde edilmiştir. Görüntülerden üretilmiş nokta bulutları üzerinden, geliştirilen I-Octree yaklaşımı ile bina detayı çıkarılması noktasında hızlı ve ucuz bir harita üretimi sürecine katkıda bulunabileceği sonucuna varılmıştır.

Keywords

Fotogrametri, Nokta Bulutu, Bina Çıkarımı, I-Octree, Sayısallaştırma

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