H. J. Sommer

Kinematic features of wheelchair propulsion

Three male paraplegics volunteered to push their wheelchairs on a motor driven treadmill, for a total of 80 min each, at a work rate of 60-65% of their VO2 maximum, determined on an earlier test session. At 20 min intervals 16 mm high-speed film of the subjects was taken for three consecutive push cycles. The digitized film was used to compute the angular kinematics of the shoulder and elbow joints, the variations in the position of the trunk (as measured by a marker on the neck) and hand relative to the axle of the rear wheel. There were no intrasubject variations over the 80 min testing period for any of the recorded variables. This was interpreted as implying that at that work rate, fatigue was not exhibited as variations in the kinematics of movement. There were considerable differences between the style of one subject when compared to the other two over all the trials of each subject. This variation in style was most obvious in subject number PT who had a pumping style of push and recovery whereas subjects CA and GW employed a more continuous circular motion. The differences in the amount of forward lean of each subject were related to residual muscle strength. The discussion centered on the influence of the different styles on performance.

Machine vision for color inspection of potatoes and apples

A machine vision system was trained to distinguish between good and greened potatoes and yellow and green ‘Golden Delicious’ apples. The method of using the HSI (Hue, Saturation, and Intensity) color system proved highly effective for color evaluation and image processing. The vision system achieved over 90% accuracy in inspection of potatoes and apples by representing features with hue histograms and applying multivariate discriminant techniques. Reducing the number of hue bins by selecting significant features only or by summing groups of hue bins increased misclassification by the vision system. Color classification represents an important quality feature evaluation method that needs to be integrated into an overall automated quality inspection and grading system.

Fourier-based Separation Technique for Shape Grading of Potatoes Using Machine Vision

A Fourier-based shape separation method was developed for shape grading of potatoes using machine vision for automated inspection. The relationship between object shape and its boundary spectrum values in Fourier domain was explored for shape extraction. A new and fast method of using Green’s theorem and boundary Fourier coefficients was given for estimating elongation of an object. A shape separator based on harmonics of the transform was defined for potato shape separation. Tests showed the shape separator was effective and efficient for difficult shape separation. The machine vision system developed has a great potential to assist humans for automated potato grading.

Grading of Mushrooms Using a Machine Vision System

The quality features of the common white Agaricus bisporus mushroom were quantified using image analysis in order to inspect and grade the mushrooms by an automated system. The features considered were color, shape, stem cut, and cap veil opening. Two human inspectors evaluated samples which were divided into training and test sets. The vision system was trained to classify mushrooms into two quality grades using thresholding. The human inspection results were compared with each other as well as the computer vision system results. Misclassification by the vision system ranged from 8 to 56% depending upon the quality feature evaluated, but averaged about 20%. The disagreement between inspectors ranged from 14 to 36%.

Comparative ontogenetic shape changes in the skull of Caiman species (Crocodylia, Alligatoridae)

Ontogenetic shape changes in the skull of three species of the genus Caiman (C. latirostris, C. sclerops, and C. yacare) are compared by geometric morphometrics for three‐dimensional configurations (the least‐squares analysis). The technique for obtaining the landmark coordinates is a simplification of the algorithm for multidimensional scaling. The ontogenetic nonlinear shape changes are similar in the three species but occur in a lesser extent in C. latirostris. These seem to be correlated with functional changes in the skull. The uniform shape change corresponds to an elongation of the skull, dorsoventral flattening, and lateral compression in C. sclerops and C. yacare. There is some lateral broadening in C. latirostris. Differences in the ontogenetic processes probably cause the differences in diet observed between C. latirostris and the other two species. Neotenic evolution seems to have acted in the skull of C. latirostris, and a posterior amplification of the early divergence led to a repatterning of the shape ontogenetic trajectory in this species. J. Morphol. 231:53–62, 1997.

Machine Vision Inspection of ‘Golden Delicious’ Apples

A machine vision system was developed to form a basis for single-pass quality feature inspection and grading of ‘Golden Delicious’ apples. The inspection criteria were based on USDA standards for fresh market apples. Image analysis algorithms were developed to assess and quantify the quality features of color, shape, and russet. Over 300 ‘Golden Delicious’ apples were inspected by the machine vision system and the results were compared to a human inspector. The vision system was able to correctly classify 100% of the apples for color, 92.3% for shape, and 82.5% for russetting.

THREE-DIMENSIONAL OSTEOMETRIC SCALING AND NORMATIVE MODELLING OF SKELETAL SEGMENTS*

Many analytical biomechanics methods require extensive three-dimensional descriptions of anatomical geometry. In particular, researchers requiring the three-dimensional coordinates of specific boney landmarks (e.g. tendon and ligament attachments) are often forced to extrapolate such measurements from an experimental specimen set to their subject geometry. This work offers an approach to two problems inherent above; accurate extrapolation of specimen landmark locations to subject homologues and statistical accumulation of normative three-dimensional anatomical landmark data bases. A least squares solution for an affine scaling transformation from specimen to subject is used which incorporates both right-left and same hand comparisons. A two stage technique is formulated to consecutively remove landmark location variation and to size a normative specimen from a set of similar specimens. This ability to statistically represent a specimen set will provide better geometric models for other analytical studies and prosthetic design and evaluation.

Determination of First and Second Order Instant Screw Parameters from Landmark Trajectories

Least squares methods were developed to determine instant screw axis (ISA) and angular acceleration axis (AAA) parameters in experimental and analytical studies. The algorithms provide linear relationships for rigid body velocity and acceleration descriptors based on position, velocity, and acceleration data for individual points on the body. Weighted least squares estimators are presented for statistical weighting on individual landmarks as well as for variance weighting to reduce systematic measurement effects. The methods include instantaneous second order screw motion which describes differential geometry of screw axodes. Two spatial mechanism examples provide recommendations for landmark count, distribution, and placement.

A technique for the calibration of instrumented spatial linkages used for biomechanical kinematic measurements

Abstract Instrumented spatial linkages (ISLs) are finding wide applications in biomechanics for measuring all six degrees of freedom of relative location and attitude between two anatomical bodies moving through limited ranges of motion. The objective of this paper is to present a calibration scheme which will re-evaluate initial estimates of various kinematic and electrical parameters describing such linkages in order to minimize the error in linkage measurements over a specified field of motion. This technique may be separated into two parts — a mechanical calibration of the overall linkage and an iterative numerical synthesis of linkage parameter estimates based upon data from the mechanical calibration. Because certain linkage parameters may not be determined with a high degree of confidence (due to component compliance, assembly, or gauging errors), numerical re-evaluation of these parameters will provide a better analytical description of the linkage and produce superior accuracy in ISL measurement calculations. Use of an accurate mechanical calibration apparatus and a non-linear regressive Marquardt optimization formulation has demonstrated the effectiveness of this technique in reevaluating such parameters and subsequently improving and estimating the accuracy of ISL measurements.

Comparison of a Neural Network and Traditional Classifier for Machine Vision Inspection of Potatoes

This work addressed the relative strengths and weaknesses of the backpropagation neural network versus the Fisher discriminant function. Their performance was compared for machine vision inspection of greening, shape, and shatter bruise in two potato cultivars. The backpropagation network’s number of hidden nodes were varied from zero to eight for each defect type to determine the optimal network classification size. The network was trained and tested five times at each hidden node number and defect type to minimize local minima variation. For greening, the best backpropagation network averaged 74.0% with three hidden nodes while the Fisher method performed with a 70.0% accuracy. The backpropagation method also performed better for shape discrimination with a 73.3% average accuracy at seven hidden layer nodes versus a 68.1% accuracy. The Fisher method performed better for shatter bruise detection with a 76.7% accuracy versus a 56.0% average accuracy at four hidden layer nodes for backpropagation.