A new image co-segmentation method using saliency detection for surveillance image of coal miners

Chen, Wei; Sun, Tongfeng; Li, Ming; Jiang, Haifeng; Zhou, Chongbo

doi:10.1016/j.compeleceng.2014.04.008

Cited by 10 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to formula (14) and (15), the evaluation indicators of precision and recall rate are negative correlation. Therefore, we use F-measure (also known as F-score) to evaluate the effectiveness of saliency detection algorithms.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…However, these algorithms have low saliency image resolutions, and their computational complexity is high at the same time. Another popular method is based on the basis of model analysis [12][13][14][15]. Although it has a good detection efficiency and the detection result coordinates well with the human eye characteristics, it cannot effectively process rich texture information in monitoring scenes.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Saliency Detection Method for Wild Animal Monitoring Images with WMSN

Feng

Zhang

et al. 2018

Journal of Sensors

View full text Add to dashboard Cite

We proposed a novel saliency detection method based on histogram contrast algorithm and images captured with WMSN (wireless multimedia sensor network) for practical wild animal monitoring purpose. Current studies on wild animal monitoring mainly focus on analyzing images with high resolution, complex background, and nonuniform illumination features. Most current visual saliency detection methods are not capable of completing the processing work. In this algorithm, we firstly smoothed the image texture and reduced the noise with the help of structure extraction method based on image total variation. After that, the saliency target edge information was obtained by Canny operator edge detection method, which will be further improved by position saliency map according to the Hanning window. In order to verify the efficiency of the proposed algorithm, field-captured wild animal images were tested by using our algorithm in terms of visual effect and detection efficiency. Compared with histogram contrast algorithm, the result shows that the rate of average precision, recall and F-measure improved by 18.38%, 19.53%, 19.06%, respectively, when processing the captured animal images.

show abstract

Section: Comparison and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Saliency Detection Method for Wild Animal Monitoring Images with WMSN

Feng

Zhang

et al. 2018

Journal of Sensors

View full text Add to dashboard Cite

show abstract

“…Hue features are consistent of skin color regions in monitoring images, although there are some changes in skin color regions of staffs. Figure 1 shows hue between the parts in the image [11].…”

Section: Features Of Humans In Monitor Imagesmentioning

confidence: 98%

Skin color modeling for face detection and segmentation: a review and a new approach

Chen

Wang

Jiang

et al. 2014

Multimed Tools Appl

Self Cite

View full text Add to dashboard Cite

Detecting skin-colored pixels, although seems a straightforward easy task, has proven to be quite a challenging task in images that are captured under complex unconstrained imaging conditions. Color segmentation is an important method of segmenting the body in images. In this paper, we first provides a review of skin color modeling research works for face detection. In particular, we focus on discussing the challenges of skin color modeling, detection, and segmentation, and then we present the skin color modeling and region-based skin segmentation. We also propose a new approach to analyze the hue characteristics of monitoring personnel in coal mine. We determine the skin color boundaries of the miners using the boundary detection method based on the response of visual hue. And then, we apply to determining hue area method using dual hue detector to segment skin color for miners. Experiments show that the method has excellent ability to segment skin regions of miners. We also summarize the most widely used methods for skin detection approaches and collecting their numerical evaluation results.

show abstract

RETRACTED ARTICLE: Saliency detection in stereoscopic images using adaptive Gaussian Kernel and Gabor filter

Rakesh

Krishna

2018

Soft Comput

View full text Add to dashboard Cite

A new image co-segmentation method using saliency detection for surveillance image of coal miners

Cited by 10 publications

References 18 publications

A Novel Saliency Detection Method for Wild Animal Monitoring Images with WMSN

A Novel Saliency Detection Method for Wild Animal Monitoring Images with WMSN

Skin color modeling for face detection and segmentation: a review and a new approach

RETRACTED ARTICLE: Saliency detection in stereoscopic images using adaptive Gaussian Kernel and Gabor filter

Contact Info

Product

Resources

About