Information visibility using transmission methods

García, J. A.; Rodrı́guez-Sánchez, Rosa; Fdez-Valdivia, J.; Martinez-Baena, J.

doi:10.1016/j.patrec.2009.12.001

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…In addition, rapid guided filtering is employed to optimize the extraction of the transmittance, so that the feature value of transmittance is more distinguishable for different air visibility levels. (3) This paper constructs a model for recognizing air visibility level based on the optimal binary tree SVM. After the calculation of the optimal binary tree and three SVMs, four air visibility levels can be recognized.…”

Section: Discussionmentioning

confidence: 99%

“…The instrumental measurement method and visual measurement method are two commonly used methods for measuring the visibility level [1,2]. In instrumental measurement method, the visibility level is usually detected using the transmission method [3] or the scattering method [4] in the optical principle. For example, Gultepe et al [5] used optical sensors to estimate the air visibility from camera images.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Method for the Recognition of Air Visibility Level Based on the Optimal Binary Tree Support Vector Machine

et al. 2018

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As the traditional methods for the recognition of air visibility level have the disadvantages of high cost, complicated operation, and the need to set markers, this paper proposes a novel method for the recognition of air visibility level based on an optimal binary tree support vector machine (SVM) using image processing techniques. Firstly, morphological processing is performed on the image. Then, whether the region of interest (ROI) is extracted is determined by the extracted feature values, that is, the contrast features and edge features are extracted in the ROI. After that, the transmittance features of red, green and blue channels (RGB) are extracted throughout the whole image. These feature values are used to construct the visibility level recognition model based on optimal binary tree SVM. The experiments are carried out to verify the proposed method. The experimental results show that the recognition accuracies of the proposed method for four levels of visibility, i.e., good air quality, mild pollution, moderate pollution, and heavy pollution, are 92.00%, 92%, 88.00%, and 100.00%, respectively, with an average recognition accuracy of 93.00%. The proposed method is compared with one-to-one SVM and one-to-many SVM in terms of training time and recognition accuracy. The experimental results show that the proposed method can distinguish four levels of visibility at a relatively satisfactory level, and it performs better than the other two methods in terms of training time and recognition accuracy. This proposed method provides an effective solution for the recognition of air visibility level.

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Section: Discussionmentioning

confidence: 99%