Date of Publication

2004

Document Type

Master's Thesis

Degree Name

Master of Science in Computer Science

Subject Categories

Computer Sciences

College

College of Computer Studies

Department/Unit

Computer Science

Thesis Adviser

Conrado D. Ruiz, Jr.

Defense Panel Chair

Florante Salvador

Defense Panel Member

Alexis Pantola
Jose Ronello Bartolome

Abstract/Summary

The proliferation of nude images is a problem that affects families, the workplace, and society in general. To address this problem, many studies in visual content security are being done. However, the current state of technology is still crude, yielding inexact results at the cost of computing power. Thus, new methods for nudity detection are being sought. In this study, a new algorithm for detecting nudity in color images is developed. A skin color distribution model is constructed using correlation and linear regression. This model is used to identify and locate skin regions in an image. These regions are analyzed for clues indicating nudity or non-nudity such as their sizes and relative distances from each other. Based on these clues and the percentage of skin in the image, an image is classified nude or non-nude. The skin color distribution model performs with 96.29% recall and 6.76% false positive rate on a test set consisting of 2,303,824 manually labeled skin pixels and 24,285,952 manually labeled non-skin pixels. The Nudity Detection Algorithm is able to detect nudity with a 94.77% recall and a false positive rate of 5.04% on a set of images consisting of 421 nude images and 635 non-nude images.

Abstract Format

html

Language

English

Format

Electronic

Accession Number

CDTG003796

Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

1 computer optical disc ; 4 3/4 in.

Keywords

Image processing; Computer vision; Nudity; Nude in art; Human figure in art--Pictorial works; Photography of the nude

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