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Related Experiment Video

Updated: Jul 7, 2026

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

Self-affine mapping system and its application to object contour extraction.

T Ida¹, Y Sambonsugi

¹Multimedia Lab., Toshiba Corp., Kawasaki. takashi.ida@toshiba.co.jp

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|February 12, 2008

Summary

This summary is machine-generated.

This study introduces a novel fractal-based contour fitting method using self-affine mapping. The algorithm accurately fits rough lines to contours, reducing manual drawing time.

Related Experiment Videos

Last Updated: Jul 7, 2026

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

Area of Science:

Computer Vision
Image Processing
Computational Geometry

Background:

Traditional contour fitting methods can be time-consuming and struggle with complex shapes.
Self-affine mapping is a technique typically used for fractal image generation.

Purpose of the Study:

To adapt self-affine mapping for accurate and efficient contour fitting.
To develop a method that handles both smooth curves and sharp corners.

Main Methods:

Utilizing a self-affine mapping system for contour fitting.
Analyzing blockwise self-similarity in grayscale images for parameter detection.
Applying mapping iterations to the boundary of an alpha mask's foreground region.

Main Results:

The method accurately fits rough lines to contours, including smooth curves and sharp corners.
It effectively extracts both distinct and blurred edges using a single parameter set.
Recursive procedures with decreasing block sizes successfully fit large gaps in contours.

Conclusions:

The proposed self-affine mapping method offers an efficient and accurate approach to contour fitting.
This technique simplifies contour drawing and edge extraction processes.
The algorithm's adaptability to various edge types and gap sizes enhances its practical utility.