2006 International Conference on Image Processing 2006
DOI: 10.1109/icip.2006.312561
|View full text |Cite
|
Sign up to set email alerts
|

An Objectionable Image Detection System Based on Region of Interest

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2

Citation Types

0
4
0

Year Published

2009
2009
2018
2018

Publication Types

Select...
4
2

Relationship

1
5

Authors

Journals

citations
Cited by 8 publications
(4 citation statements)
references
References 10 publications
0
4
0
Order By: Relevance
“…The center point of salient region is the centroid of saliency map and there is the relationship between the size of saliency region and the 1 st order central moment of saliency map [8]. Therefore, the size of salient region is calculated using the 1 st order central moment of saliency map as following equation: (4) where α is the constant, w' and h' are the 1 st order central moment of saliency map along the x and y direction respectively.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…The center point of salient region is the centroid of saliency map and there is the relationship between the size of saliency region and the 1 st order central moment of saliency map [8]. Therefore, the size of salient region is calculated using the 1 st order central moment of saliency map as following equation: (4) where α is the constant, w' and h' are the 1 st order central moment of saliency map along the x and y direction respectively.…”
Section: Introductionmentioning
confidence: 99%
“…Figure 1. From left to right: input image, saliency map using the method presented by Achanta et al [8], skin information combined saliency map, results of our salient region detection.…”
Section: Introductionmentioning
confidence: 99%
“…The detecting results are stored in the memory layer, and help the perceptual layer to detect the temporal static objects. In addition, (Jeong, 2006) proposes an objectionable image detection system based on the R O I . T h e s y s t e m p r o p o s e d b y ( J e o n g , 2 0 0 6 ) e x c e l s i n t h a t R O I d e t e c t i o n m e t h o d i s specialized in objectionable image detection.…”
Section: Object Detectionmentioning
confidence: 99%
“…In addition, a novel feature consisting of weighted SCD based on ROI and skin color structure descriptor is presented for classifying objectionable image. Using the ROI detection method, (Jeong, 2006) can reduce the noisy information in image and extract more accurate features for classifying objectionable image. Further, (Lin et al, 2005) uses genetic programming (GP) to synthesize composite operators and composite features from combinations of primitive operations and primitive features for object detection.…”
Section: Object Detectionmentioning
confidence: 99%