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  • 2018 International Conference on Image and Vision Computing New Zealand, IVCNZ 2018; Auckland, New Zealand; 19th-21st November 2018 Vol. 2018-November, p. 1-6
Full Text
1No 1Yes
Creator
1Aryal, Sunil 1Karmakar, Gour 1Lu, Guojun 1Murshed, Manzur 1Shojanazeri, Hamid 1Tania, Sheikh 1Zhang, Dengsheng
Subject
1Cuboid segmentation 1Dissimilarity measure 1Image dissimilarity 1Image retrieval 1Infinity norm 1Perceptual dissimilarity 1Segmentation quality metric
Format Type
1Adobe Acrobat PDF
Resource Type
1Conference paper
Facets
Full Text
1No 1Yes
Creator
1Aryal, Sunil 1Karmakar, Gour 1Lu, Guojun 1Murshed, Manzur 1Shojanazeri, Hamid 1Tania, Sheikh 1Zhang, Dengsheng
Subject
1Cuboid segmentation 1Dissimilarity measure 1Image dissimilarity 1Image retrieval 1Infinity norm 1Perceptual dissimilarity 1Segmentation quality metric
Format Type
1Adobe Acrobat PDF
Resource Type
1Conference paper
  • Title
  • Creator
  • Date

A novel perceptual dissimilarity measure for image retrieval

- Shojanazeri, Hamid, Zhang, Dengsheng, Teng, Shyh, Aryal, Sunil, Lu, Guojun

  • Authors: Shojanazeri, Hamid , Zhang, Dengsheng , Teng, Shyh , Aryal, Sunil , Lu, Guojun
  • Date: 2018
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 2018 International Conference on Image and Vision Computing New Zealand, IVCNZ 2018; Auckland, New Zealand; 19th-21st November 2018 Vol. 2018-November, p. 1-6
  • Full Text: false
  • Reviewed:
  • Description: Similarity measure is an important research topic in image classification and retrieval. Given a type of image features, a good similarity measure should be able to retrieve similar images from the database while discard irrelevant images from the retrieval. Similarity measures in literature are typically distance based which measure the spatial distance between two feature vectors in high dimensional feature space. However, this type of similarity measures do not have any perceptual meaning and ignore the neighborhood influence in the similarity decision making process. In this paper, we propose a novel dissimilarity measure, which can measure both the distance and perceptual similarity of two image features in feature space. Results show the proposed similarity measure has a significant improvement over the traditional distance based similarity measure commonly used in literature.
  • Description: International Conference Image and Vision Computing New Zealand
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Cuboid colour image segmentation using intuitive distance measure

- Tania, Sheikh, Murshed, Manzur, Teng, Shyh, Karmakar, Gour


  • Authors: Tania, Sheikh , Murshed, Manzur , Teng, Shyh , Karmakar, Gour
  • Date: 2018
  • Type: Text , Conference proceedings
  • Relation: 2018 International Conference on Image and Vision Computing New Zealand, IVCNZ 2018; Auckland, New Zealand; 19th-21st November 2018 Vol. 2018-November, p. 1-6
  • Full Text:
  • Reviewed:
  • Description: In this paper, an improved algorithm for cuboid image segmentation is proposed. To address the two main limitations of the recently proposed cuboid segmentation algorithm, the improved algorithm substitutes colour quantization in HCL colour space with infinity norm distance in RGB colour space along with a different way to impose area thresholding. We also propose a new metric to evaluate the quality of segmentation. Experimental results show that the proposed cuboid segmentation algorithm significantly outperforms the existing cuboid segmentation algorithm in terms of quality of segmentation.
  • Description: International Conference Image and Vision Computing New Zealand

Cuboid colour image segmentation using intuitive distance measure

  • Authors: Tania, Sheikh , Murshed, Manzur , Teng, Shyh , Karmakar, Gour
  • Date: 2018
  • Type: Text , Conference proceedings
  • Relation: 2018 International Conference on Image and Vision Computing New Zealand, IVCNZ 2018; Auckland, New Zealand; 19th-21st November 2018 Vol. 2018-November, p. 1-6
  • Full Text:
  • Reviewed:
  • Description: In this paper, an improved algorithm for cuboid image segmentation is proposed. To address the two main limitations of the recently proposed cuboid segmentation algorithm, the improved algorithm substitutes colour quantization in HCL colour space with infinity norm distance in RGB colour space along with a different way to impose area thresholding. We also propose a new metric to evaluate the quality of segmentation. Experimental results show that the proposed cuboid segmentation algorithm significantly outperforms the existing cuboid segmentation algorithm in terms of quality of segmentation.
  • Description: International Conference Image and Vision Computing New Zealand

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