Determination of RQD by digital image analysis

2018
Sarıçam, İ. Turgut
Digital image processing and analysis methods allow us to automate routine tasks. Rock Quality Designation (RQD) is a rock quality index used in rock mechanics and geotechnical designs of slopes and underground excavations. Manual logging of hundreds of meters of rock core samples with a tape measure is a very laboursome and tedious process. In this research study, a method is introduced for the segmentation of cores and the determination of RQD from digital images of rows of core samples in core boxes in order to compute RQD in an automatic way by finding and locating natural fractures in cores and measuring intact core lengths. First, three digital true color images of a core box, with the same camera position but different light source positions, are taken using a high resolution camera. After the detection of the core box with color thresholding, the sections of the box are detected by using Hough transform and boundary tracing algorithms. Then, the cores are extracted from each section using color thresholding. After cleaning the shadows created by different light sources using various techniques, the segmentation part is finished by combining similar regions with each other. Later, non-cylindrical parts of the cores are detected by looking at the changes caused by two different light sources. After completion of the fracture detection in the drill core, RQD is calculated by measuring the valid centerline lengths of each core. All coding routines are developed in MATLAB 2017a. Two different core boxes with 4 and 5 rows storing HQ and NQ diameter cores having various joint/bedding plane angles are photographed several times with different core placements. It is shown that the method is capable of separating even tightly fit joint surface cores. Moreover, it can successfully detect non-cylindrical parts of the cores, and avoid small or irregularly shaped ones which should not be included in RQD calculation.

Suggestions

Alignment of uncalibrated images for multi-view classification
Arık, Sercan Ömer; Vural, Elif; Frossard, Pascal (2011-12-29)
Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pairwise similarity measure between images, where a common choice is the Euclidean distance. However, the accuracy of the Euclidean distance as a similarity measure is restricted to cases where images are captured from nearby viewpoints. In settings with large transformations and viewpoint changes, alignment of im...
Image annotation with semi-supervised clustering
Sayar, Ahmet; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2009)
Image annotation is defined as generating a set of textual words for a given image, learning from the available training data consisting of visual image content and annotation words. Methods developed for image annotation usually make use of region clustering algorithms to quantize the visual information. Visual codebooks are generated from the region clusters of low level visual features. These codebooks are then, matched with the words of the text document related to the image, in various ways. In this th...
Matching of straight line segments from aerial stereo images of urban areas
Ok, Ali Ozgun; Wegner, Jan Dirk; Heipke, Christian; Rottensteiner, Franz; Soergel, Uwe; Toprak, Vedat (2012-11-01)
Reliable extraction of corresponding straight lines in overlapping images can be used for different purposes such as 3D object extraction, image registration, automated triangulation, etc. In this study, a new approach for the matching of straight line features from stereo aerial images is presented. Initial correspondences between stereo images are generated using a pair-wise stereo matching approach, which involves a total of seven relational constraints. The final straight line correspondences between th...
Optimization of time-cost-resource trade-off problems in project scheduling using meta-heuristic algorithms
Bettemir, Önder Halis; Sönmez, Rifat; Department of Civil Engineering (2009)
In this thesis, meta-heuristic algorithms are developed to obtain optimum or near optimum solutions for the time-cost-resource trade-off and resource leveling problems in project scheduling. Time cost trade-off, resource leveling, single-mode resource constrained project scheduling, multi-mode resource constrained project scheduling and resource constrained time cost trade-off problems are analyzed. Genetic algorithm simulated annealing, quantum simulated annealing, memetic algorithm, variable neighborhood ...
Optical flow based video frame segmentation and segment classification
Akpınar, Samet; Alpaslan, Ferda Nur; Department of Computer Engineering (2018)
Video information retrieval is a field of multimedia research enabling us to extract desired semantic information from video data. In content-based video information retrieval, visual content obtained from video scenes is utilized. For developing methods to cope with content-based video information retrieval in terms of temporal concepts such as action, event, etc., representation of temporal information becomes critical. In this thesis, action detection is tackled based on a temporal video representation m...
Citation Formats
İ. T. Sarıçam, “Determination of RQD by digital image analysis,” M.S. - Master of Science, Middle East Technical University, 2018.