Efficient Use of MPEG‐7 Edge Histogram Descriptor

By C. Won, D. Park, Soo-Jun Park. 2002

389 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/c14fa910dc69a5a2646f0335dad5c4a95f7f3f49

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Yiannis S. Boutalis
2. Priscila Tiemi Maeda Saito
3. Savvas A Chatzichristofis
4. Pedro Henrique Bugatti
5. Rafael Staiger Bressan
6. Guanghai Liu
7. Lucas M. Valério
8. Jing-yu Yang

Citations in the corpus

• CEDD: Color and Edge Directivity Descriptor: A Compact Descriptor for Image Indexing and Retrieval (2008, methodology): “Query (Image Number) / NMRR Values for the Descriptors DCD SCD CLD CSD EHD HTD CEDD 600 0.5273 0.0828 0.4543 0.0658 0.2771 0.4451 0.04798 327 0.3363 0.4063 0.5419 0.3477 0.3172 0.5944 0.12015 102 0.3893 0.5668 0.3697 0.4923 0.4684 0.9355 0.27547 204 0.4039 0.4417 0.6164 0.3228 0.7817 0.8867 0.29035 ”
• Content-based image retrieval using color difference histogram (2013, methodology): “The computation of this descriptor is straightforward and generates a histogram of the main edge directions within blocks of fixed size [42].”
• DOCToR: The Role of Deep Features in Content-Based Mammographic Image Retrieval (2018, methodology): “Feature Extractor Category #Features BIC Histogram [15] Color 512 Edge Histogram [16] Color 150 Normalized Histogram [17] Color 256 Haralick [18] Texture 24 Rotation Invariant LBP [19] Texture 108 Texture Spectrum [20] Texture 8 Daubechies [21] Shape 16 Haar [21] Shape 16 Zernike [22] Shape 36”