Detection of local objects of interest in images by using multiscale relevance function

Roman M. Palenichka; Yuri B. Rytsar

doi:10.1117/12.395084

4 August 2000 Detection of local objects of interest in images by using multiscale relevance function

Roman M. Palenichka, Yuri B. Rytsar

Proceedings Volume 4052, Signal Processing, Sensor Fusion, and Target Recognition IX; (2000) https://doi.org/10.1117/12.395084
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

The reliable detection of objects of interest on inhomogeneous background base don image data is a typical detection and recognition problem in many practical applications. In this paper, an algorithm of local object detection is described in the context of change detection based on the difference between two images obtained from the same scene. The proposed detection method using multi-scale relevance function is a model based-approach which takes into account the planar shape model of objects of interest and the regression model of intensity function with respect to objects and background. The image relevance function is an image local operator whose local extrema indicate on the locations of objects or their salient parts termed as primitive patterns. The image fragment centered at the maximum point of the relevance function represents a region of attention. A structure-adaptive binarizaiton is performed within each region of attention by using variable threshold. The comparative testing of the proposed algorithm and the known techniques have shown better performance of the relevance function approach at the approximately same dely of detection.

Citation Download Citation

Roman M. Palenichka and Yuri B. Rytsar "Detection of local objects of interest in images by using multiscale relevance function", Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); https://doi.org/10.1117/12.395084

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available