3DK3DK - - April 21, 2023April 21, 2023 ( (11))

PURSUING MECHANICAL PART FEATURE RECOGNITION

THROUGH THE ISOLATION OF 3D FEATURES IN ORGANIC SHAPES

IMECE 2002 Conference –New Orleans

Suraj Mohandas

Mark R. Henderson

3DK3DK - - April 21, 2023April 21, 2023 ( (22))

CONTENTS OF THE PRESENTATION

Feature Recognition BasicsImproving Feature RecognitionSegmentation and Classification of Geometric

ModelsResultsConclusionsFuture Goals

3DK3DK - - April 21, 2023April 21, 2023 ( (33))

Introduction

Conventional Feature Recognition of prismatic shapes has had mixed results

Hypothesis: If we can classify complex organic shapes, it may help in classifying simpler engineering shapes

Goal: Develop a method to classify organic shapesResults: Can improve future feature recognition

strategies

3DK3DK - - April 21, 2023April 21, 2023 ( (44))

Common Feature Recognition Strategies

Volume Decomposition Graph-matching Algorithms AI-based and rule-based systems Geometric reasoning Neural nets

Feature Recognition is still an unsolved problem

3DK3DK - - April 21, 2023April 21, 2023 ( (66))

Why Does It Fail ?

Interacting FeaturesWhen Complex real-world

parts are involved hundreds of surfaces lots of curves hundreds of features

From “Feature Recognition for Process Planning: A Status Report - William C. Regli , Mike Pratt Jung Hyun Han”

Organic shapes possess these and other characteristics

3DK3DK - - April 21, 2023April 21, 2023 ( (77))

Putting The Features To Work

DEFINITION: Features are curvature-based regions on a 3D triangulated and subdivided object

GOAL: Extract an overall shape signature

Method: Divide and Conquer Ultimately, re-assemble the

classified regions to recognize complete shapes

3DK3DK - - April 21, 2023April 21, 2023 ( (88))

The Femur Region subdivision is Dependent on a parameter (Threshold) Study to investigate optimal Threshold values for desired Subdivisions What is the desired subdivision ?

3DK3DK - - April 21, 2023April 21, 2023 ( (99))

Generating Regions

STEPS:

Multiple Scanning Merging -> Triangular meshOptional DecimationWatershed (Mangan & Whitaker)

3DK3DK - - April 21, 2023April 21, 2023 ( (1010))

A Little Anatomy

Major Trochanter (Protrusion)

Minor Trochanter

Supracondyloid Fossa (Depression)

Bone organic features are irregular in

nature.

3DK3DK - - April 21, 2023April 21, 2023 ( (1111))

A Little Anatomy

Medial Condyle

Lateral Condyle

3DK3DK - - April 21, 2023April 21, 2023 ( (1212))

A Little Anatomy

Head

NeckFovea Capitus

3DK3DK - - April 21, 2023April 21, 2023 ( (1313))

A Little Anatomy

3DK3DK - - April 21, 2023April 21, 2023 ( (1414))

Mechanical Part

Parts Generated In Acis® Modeler and Then Subjected to

Watershed

3DK3DK - - April 21, 2023April 21, 2023 ( (1515))

Segmentation using Watershed

Segmentation threshold is key in the separation of the object into features

Calculate curvature based on the triangulated model Curvatures available are Principal curvatures,

Gaussian curvature, mean, RMS, absolute, etc. Step 1: Curvature Calculation

3DK3DK - - April 21, 2023April 21, 2023 ( (1616))

Significance Of Threshold

Threshold Defined as the watershed depth Determines number of regions on object

Resulting Region definition is sensitive to the Threshold value

Step – Try Individual threshold values for individual regions

3DK3DK - - April 21, 2023April 21, 2023 ( (1717))

WATERSHED STEPS

Labeling Of Local Minima

Flat Plateau

Flat Minimum

Labeling Flat Region

OR

Bottom Up Approach

Top Down Approach *

OR

Step 2

Step 3

3DK3DK - - April 21, 2023April 21, 2023 ( (1818))

WATERSHED MERGING (Final Step)

Watershed Depth

Vertex Of Current Region

Vertex Of Neighboring Region

Merging Adjacent Regions With Shallow Depths

Threshold

3DK3DK - - April 21, 2023April 21, 2023 ( (1919))

Effect Of Threshold

0.001 0.025 0.1 0.5

3DK3DK - - April 21, 2023April 21, 2023 ( (2020))

Results & Conclusions

Feature Snapshot Threshold Value

BEST

Head & Fovea

Capitus

0.14945 – 0.19990

WORST

Trochantic Fossa

0.11301- 0.12246

3DK3DK - - April 21, 2023April 21, 2023 ( (2121))

Best and Worst Subdivision Results

BEST RESULT: Good correlation to the actual anatomical feature

for a given threshold range.

WORST RESULT: Poor correlation to the actual anatomical feature at

any threshold

3DK3DK - - April 21, 2023April 21, 2023 ( (2222))

Results & Conclusions

Feature Snapshot Threshold Value

Neck 0.26127 - 0.27894

Minor

Trochanter

0.05331 - 0.05907

3DK3DK - - April 21, 2023April 21, 2023 ( (2323))

Results & Conclusions

Decimation changes regions loss of important curvature data granularity.

Some features were more easily picked up than others Some feature segmentations (e.g., large depressions - fossae)

less sensitive to threshold variation. Difficult to predict the optimal threshold – it depends on the

segment desired Threshold range can be predicted for similar features on two

similar types of objects Can predict good threshold ranges through experience

3DK3DK - - April 21, 2023April 21, 2023 ( (2424))

Using the Segments to Create the Feature Signature

Array of Single Value Scale & Orientation Invariant Parameters

calculated from the region geometry

Metric 1 Metric 2 Metric 3 Metric (n-1) Metric n

Assuming a good subdivision, for each region calculate a Shape Signature

Shape Signature Vector Definition:

3DK3DK - - April 21, 2023April 21, 2023 ( (2525))

Future

Develop method to predict optimal feature extraction thresholds for desired features.

Predict decimation limitCluster shape signatures to classify shape

3DK3DK - - April 21, 2023April 21, 2023 ( (2626))

Acknowledgements

The Students and Faculty in the “Partnership for Research In Spatial Modeling”- PRISM at Arizona State University

Myungsoo Bae (PhD Candidate ASU) – Interface design