Image motion processing in biological and computer vision systems

Abdesselam Bouzerdoum, Robert B. Pinter

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Motion modeling in biological and computer vision systems is divided into two categories: Intensity-based schemes and feature-matching schemes. Some models from each category are discussed. Intensity-based models are further subdivided into global and local models. Moreover, a new motion detection model that belongs to the family of intensity-based schemes is introduced. The model operates on the same basic structure as the Reichardt’s correlation model does, that is, a nonlinear asymmetric interaction between signals from two adjacent channels. However, the new model differs from that of Reichardt in the nature and origin of the nonlinear interaction: It is of the inhibitory type originating from the biophysical mechanism of shunting inhibition. Our model detects fairly well motion of objects like edges and bars. Furthermore, its mean response to a moving grating of low contrast is equivalent to that of the Reichardt correlation model.

Original languageEnglish
Pages (from-to)1229-1241
Number of pages13
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume1199
DOIs
Publication statusPublished - 1 Nov 1989
Externally publishedYes

Fingerprint

Dive into the research topics of 'Image motion processing in biological and computer vision systems'. Together they form a unique fingerprint.

Cite this