Perceptually-Weighted Evaluation Criteria for Segmentation Masks in Video Sequences

Villegas, Paulo; Marichal, Xavier

doi:10.1109/tip.2004.828433

Cited by 71 publications

(81 citation statements)

References 7 publications

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“…The combined objective metrics for segmentation evaluation in [6,7,8,9] were determined empirically. In comparison, the weighing parameters of the new composite metric were computed by quantitatively correlating the objective and subjective measures.…”

Section: Discussionmentioning

confidence: 99%

“…Compared to the subjective evaluation, the objective metrics are easy to compute, but may not provide an overall assessment of the segmentation quality because each metric only captures certain aspect of the difference between the segmentation and the ground truth. Recently, several methods based on combined objective metrics have been proposed to provide evaluation more relevant to subjective assessment of generic object segmentation [6,7,8,9]. The weights in these combined measures, however, are determined rather empirically, and may not be applicable for tumor segmentation evaluation due to the medical expertise required in the assessment.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On Simulating Subjective Evaluation Using Combined Objective Metrics for Validation of 3D Tumor Segmentation

Deng

Zhu

Sun

et al. 2007

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007

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Abstract. In this paper, we present a new segmentation evaluation method that can simulate radiologist's subjective assessment of 3D tumor segmentation in CT images. The method uses a new metric defined as a linear combination of a set of commonly used objective metrics. The weighing parameters of the linear combination are determined by maximizing the rank correlation between radiologist's subjective rating and objective measurements. Experimental results on 93 lesions demonstrate that the new composite metric shows better performance in segmentation evaluation than each individual objective metric. Also, segmentation rating using the composite metric compares well with radiologist's subjective evaluation. Our method has the potential to facilitate the development of new tumor segmentation algorithms and assist large scale segmentation evaluation studies.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On Simulating Subjective Evaluation Using Combined Objective Metrics for Validation of 3D Tumor Segmentation

Deng

Zhu

Sun

et al. 2007

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007

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show abstract

“…Also, slight differences in the extraction from frame to frame can lead to a lack of temporal coherence, which further resulting in a jittery video. Because human visualization system (HVS) is very sensitive to temporal inconsistencies [49], advanced algorithm is needed for video matting for future research.…”

Section: Future Workmentioning

confidence: 99%

Color range determination and alpha matting for color images

Zhi-Quan

Wang

Zhao

et al. 2013

2013 IEEE International Conference on Imaging Systems and Techniques (IST)

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This thesis proposes a new chroma keying method that can automatically detect background, foreground, and unknown regions. For background color detection, we use K-means clustering in color space to calculate the limited number of clusters of background colors. We use spatial information to clean the background regions and minimize the unknown regions. Our method only needs minimum inputs from user.For unknown regions, we implement the alpha matte based on Wang's robust matting algorithm, which is considered one of the best algorithms in the literature, if not the best. Wang's algorithm is based on modified random walk. We proposed a better color selection method, which improves matting results in the experiments. In the thesis, a detailed implementation of robust matting is provided.The experimental results demonstrate that our proposed method can handle images with one background color, images with gridded background, and images with difficult regions such as complex hair stripes and semi-transparent clothes.i

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“…In [2] a procedure for evaluating the intrinsic quality of segmentation masks in video sequences where the existence of ground-truth masks is assumed is proposed. The procedure adopted in MPEG-4 for objective and automatic evaluation is described in [3].…”

Section: Introductionmentioning

confidence: 99%

Design of Statistical Measures for the Assessment of Image Segmentation Schemes

Droogenbroeck

Barnich

2005

Computer Analysis of Images and Patterns

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Image segmentation is discussed for years in numerous papers, but assessing its quality is mainly dealt with in recent works. Quality assessment is a primary concern for anyone working towards better segmentation tools. It both helps to objectively improve segmentation techniques and to compare performances with respect to other similar algorithms. In this paper we use a statistical framework to propose statistical measures capable to describe the performances of a segmentation scheme. All the measures rely on a ground-truth segmentation map that is supposed to be known and that serves as a reference when qualifying the results of any segmentation tool. We derive the analytical expression of several transition probabilities and show how to calculate them. An important conclusion from our study, often overlooked, is that performances can be content dependent, which means that one should adapt a measure to the content of an image.

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Perceptually-Weighted Evaluation Criteria for Segmentation Masks in Video Sequences

Cited by 71 publications

References 7 publications

On Simulating Subjective Evaluation Using Combined Objective Metrics for Validation of 3D Tumor Segmentation

On Simulating Subjective Evaluation Using Combined Objective Metrics for Validation of 3D Tumor Segmentation

Color range determination and alpha matting for color images

Design of Statistical Measures for the Assessment of Image Segmentation Schemes

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