An improved color cast feature and feature extraction method based on lab chromaticity histogram

Zou, Xiaochun; Shen, Zhixi; Kang, Jie; Dai, Donglin

doi:10.1109/siprocess.2016.7888237

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…We compare the MGW method with the grey world [3] and equivalent circle algorithm [9] for accuracy (Table 3). We observe that the MGW method has the smallest false acceptance rate (FAR) and false rejection rate (FRR).…”

Section: Experiments and Comparisonmentioning

confidence: 99%

“…Many methods have been developed to detect and restore colour cast images in the literature such as grey world [3, 4], white patch [5, 6], neural network [7, 8], equivalent circle algorithm [9] and so on. Grey world method calculates weighting values in red, green and blue (RGB) colour space for colour correction by matching the colour average with a grey reference value.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, its performance depends on the quality of prior knowledge and the structure of the neural network. Equivalent circle algorithm [9] also demonstrates modest performance when multiple colour cast exist one single image.…”

Section: Introductionmentioning

confidence: 99%

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Modified grey world method to detect and restore colour cast images

Liu

Chen

2019

IET Image Processing

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This study proposes a new, simple but effective technique to detect and restore colour cast images, named modified grey world method. This method detects colour cast images of outdoor surveillance videos by computing the values in the YUV colour space, which makes it much easier than classic methods. Specific colour cast can be found out by calculating the hue values. Additionally, this method can detect not only simple colour cast images but also multiple colour cast images simultaneously. To detect and restore a colour cast image, the authors first remove all grey pixels and separate it into multiple parts with a maze-solving algorithm. Then, they compute the YUV colour values of each part. If the values are too high or too low, this part of the input image is designated as a colour cast. Finally, they carry out a restoration procedure, in which they calculate weights by matching average colour value with a grey reference value in YUV colour space. This method has been tested in the Safety City surveillance system in Wuhan city, China. The results show that the proposed method leads to better results in detecting and restoring colour cast imaging than classic methods in outdoor surveillance videos.

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Section: Experiments and Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modified grey world method to detect and restore colour cast images

Liu

Chen

2019

IET Image Processing

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Fast Two-Cycle Level Set Tracking With Interactive Superpixel Segmentation and Its Application in Image Retrieval

Pan

et al. 2019

IEEE Access

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In this paper, a fast two-cycle level set contour tracking algorithm based on interactive superpixel segmentation is proposed. Then, image retrieval is carried out based on the contour tracking results. The method of contour tracking is divided into three stages: superpixel segmentation, interactive feature extraction, and foreground tracking. In the first phase, the image is preprocessed by a superpixel segmentation method. In the second stage, the feature pools are defined and established interactively according to the complexity of the image. In the last stage, based on the first two stages, a fast two-cycle level set method is used to track the contour of the target object. Finally, the results of the contour tracking are applied to an image matting of the target foreground, and then the foreground image retrieval is implemented. The results of experimental comparisons demonstrate the effectiveness of the proposed method.

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