In the area of deer antler evaluation for trophy homologation, as well as in the obtaining of biometric databases for later analysis in the field of Geometric Morphometrics, different linear ...biometric tools have traditionally been used. In this study we used two sets of antlers from 29 Iberian red deer (Cervus elaphus hispanicus) to develop and establish a new photogrammetric technique which creates the 3D model of the antler using a parametric 3D Computer-Aided Design (CAD). This simple and reliable method for deer hunting trophy homologation was compared with the other two more extensively used methods of antler measurement, the traditional measuring tape and the Articulated Arm Coordinate Measuring Machine (AACMM or CMA).
The advantage of this innovative photogrammetric method is the use of only two photographs to obtain both the 3D model and the dimensions required for antler evaluation. A procedure was performed to compare lengths and antler evaluation as hunting trophy. The three methods showed similar reliability, although the photogrammetric process using the 3D CAD system was much faster and more functional than both the traditional measuring tape and Articulated Arm methods. Since this method only requires two photographs per individual, it makes possible the study of a high percentage of antlers in the field.
This new photogrammetric method has been successfully used in the biometrics area, but it could become a more extensively used method in this and other fields because of its ease of operation, speed and accuracy of data collection.
•Antlers photogrammetric modelling and measuring by ray-tracing in parametric CAD-3D.•Two photographs per deer. Easy change of the photographs fitting new ray-tracing.•Fast way to obtain geometric data on high number of specimens in field conditions.•Same results with new method than other as tape and Coordinate Measuring Machines.
Traditionally cartographic methods (i.e. photogrammetry) have been the way to data capture, but nowadays collaborative cartography deserves attention since everybody can edit and share its own data ...coming from GPS or similar. So a method to improve the precision of the collaborative cartography, particularly terrestrial transportation ways, has become useful and of general interest. In our study we use some polygonals in X, Y, Z coordinates which people capture with low accuracy GPS bring in their automobiles. For the same road we can have hundreds of traces coming from different dates and people. We aim to improve the accuracy computing a sort of mean of all the traces by using two different methods (discrete Fréchet distance is implemented starting with both the nearest and the farthest neighbors). After each solution is computed, a comparative between them is analyzed by using a B-Spline fitting procedure. The developed method to compare our two solutions can be also applied between these solutions and some ideal measurements.
3-D calibration for freehand Ultrasound (US) image is an extremely important technique to build up 3-D US image system in ultrasound Non-destructive Testing (NDT). Calibration is a procedure to ...calculate the spatial transformation matrix, spatial relationship between the US image plane and the tracker attached to the US probe. In this research, a different cross-string phantom and the corresponding algorithm are investigated. The strings and crosses out of the scanning plane in the phantom accelerate interactive operation speed, guiding the operator to find the scanning plane quickly. Furthermore, the ten crosses in the scanning plane provide the coordinates and spatial vectors for the calibration algorithm, thus the different calibration algorithm based on the least-squares fitting method of the homologous points matching can be realized. The precision and the accuracy results show that the algorithm calculates more accurate calibration matrix than that is obtained through the other published methods in the same operating time. The results solve the obligatory pre-procedure for computerize 3-D freehand ultrasonic in NDT.
A number of geometrical methods for comparing shapes have been developed recently. This paper explores two approaches for analyzing the morphological variation of some invertebrate fossil ...characteristics such as rib pattern and whorl section shape: (1) landmarks analysis (Procrustes methods), (2) mathematical modeling by Fourier analysis.
The morphometric analysis has been applied to a faunal sequence of Graphoceratidae (Ammonitina) taken in the central High Atlas.
In the first stage of analysis, we used landmarks to describe shapes. This calculation is done through the “Procrustes” program whose results generate phenetic trees with a typically morphological significance and whose nodes convey some degrees of morphological similarities among the different taxa analyzed.
In the second stage of describing ammonite shape, a new approach will offer us a valuable morphologic descriptor by modeling the whorl section. It allows for transcription in the form and an equation will be used for descriptive variables which represent necessary data for an analysis in principal components. Factorial planes then correspond to morphological space within which the analyzed individuals are distributed.
In this way, it is possible to determine the groups for which whorl section morphologies show similarities.
These two morphometric techniques offer a valuable tool for the analysis and comparison of morphologies for both rib shape and whorl section. This allows one not only to analyze morphological diversity in Graphoceratidae with more reliability, but also to highlight the most important convergences among the analyzed taxa.
Finding Homologous Points Goshtasby, Arthur Ardeshir
Theory and Applications of Image Registration,
2017, 2017-08-07
Book Chapter
Finding homologous points in two images of a scene is the first step in determining the parameters of a transformation model that will ultimately register the images. This chapter describes various ...methods for finding homologous points in two images of a scene. When a set of points in each image is given and it is required to find correspondence between the points, the problem becomes one of point pattern matching and is covered. If the type of transformation model relating the points is known, the parameters of the transformation can be determined by clustering or random sample consensus (RANSAC). The also chapter covers these topics. It further describes template matching, and discusses various similarity and distance measures used in template matching. Search strategies in template matching include coarse‐to‐fine matching, multistage matching, rotationally invariant matching, and Gaussian‐weighted matching.
Volume Image Registration Goshtasby, Arthur Ardeshir
Theory and Applications of Image Registration,
2017, 2017-08-07
Book Chapter
This chapter first discusses methods for detecting feature points in volumetric images. Then, it details methods for determining homologous points in images are detailed. To account for local ...geometric differences between the given images, a coarse‐to‐fine search is taken. The coarse‐to‐fine search strategy not only speeds up the correspondence process but also reduces the number of outliers. Next, the chapter describes various transformation models for registration of volumetric images and given examples of volume image registration. Volume spline and weighted rigid transformations are used to register volumetric images. A volume spline transformation uses some global interpolation functions, while a weighted rigid transformation uses some locally sensitive approximation functions. The key performance measures in registration software are accuracy, reliability, and speed. The chapter further describes methods to determine these performance measures in volumetric image registration. Finally, the chapter reviews literature relating to volume image registration.
Surgical cameras are prevalent in modern operating theatres and are often used as a surrogate for direct vision. Visualisation techniques (e.g. image fusion) made possible by tracking the camera ...require accurate hand–eye calibration between the camera and the tracking system. The authors introduce the concept of ‘guided hand–eye calibration’, where calibration measurements are facilitated by a target registration error (TRE) model. They formulate hand–eye calibration as a registration problem between homologous point–line pairs. For each measurement, the position of a monochromatic ball-tip stylus (a point) and its projection onto the image (a line) is recorded, and the TRE of the resulting calibration is predicted using a TRE model. The TRE model is then used to guide the placement of the calibration tool, so that the subsequent measurement minimises the predicted TRE. Assessing TRE after each measurement produces accurate calibration using a minimal number of measurements. As a proof of principle, they evaluated guided calibration using a webcam and an endoscopic camera. Their endoscopic camera results suggest that millimetre TRE is achievable when at least 15 measurements are acquired with the tracker sensor ∼80 cm away on the laparoscope handle for a target ∼20 cm away from the camera.
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