The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
A Survey of Shape Feature Extraction Techniques
Open accessAbstract
"A picture is worth one thousand words". This proverb comes from Confucius a Chinese philosopher before about 2500 years ago. Now, the essence of these words is universally understood. A picture can be magical in its ability to quickly communicate a complex story or a set of ideas that can be recalled by the viewer later in time. Visual information plays an important role in our society, it will play an increasingly pervasive role in our lives, and there will be a growing need to have these sources processed further. The pictures or images are used in many application areas like architectural and engineering design, fashion, journalism, advertising, entertainment, etc. Thus it provides the necessary opportunity for us to use the abundance of images. However, the knowledge will be useless if one can't _nd it. In the face of the substantive and increasing apace images, how to search and to retrieve the images that we interested with facility is a fatal problem: it brings a necessity for image retrieval systems. As we know, visual features of the images provide a description of their content. Content-based image retrieval (CBIR), emerged as a promising mean for retrieving images and browsing large images databases. CBIR has been a topic of intensive research in recent years. It is the process of retrieving images from a collection based on automatically extracted features.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Visual pattern recognition by moment invariants
Hu, M.-K. (1962) · IEEE Transactions on Information Theory · doi:10.1109/tit.1962.1057692 · Cited by 7,546
Shape matching and object recognition using shape contexts
Belongie, S., Malik, J., & Puzicha, J. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.993558 · Cited by 6,306
Image Processing, Analysis and Machine Vision
Sonka, M., Hlavac, V., & Boyle, R. (1993) · Springer eBooks · doi:10.1007/978-1-4899-3216-7 · Cited by 3,717
(1986) · Cited by 3,616
Distance transformations in digital images
Borgefors, G. (1986) · Computer Vision, Graphics, and Image Processing · doi:10.1016/s0734-189x(86)80047-0 · Cited by 1,898
Review of shape representation and description techniques
Zhang, D., & Lu, G. (2004) · Pattern Recognition · doi:10.1016/j.patcog.2003.07.008 · Cited by 1,867
Fourier Descriptors for Plane Closed Curves
Zahn, C. T., & Roskies, R. Z. (1972) · IEEE Transactions on Computers · doi:10.1109/tc.1972.5008949 · Cited by 1,860
Physiological effects of humic substances on higher plants
Nardi, S., Pizzeghello, D., Muscolo, A., & Vianello, A. (2002) · Soil Biology and Biochemistry · doi:10.1016/s0038-0717(02)00174-8 · Cited by 1,138
Nitrate: nutrient and signal for plant growth.
Crawford, N. M. (1995) · The Plant Cell · doi:10.1105/tpc.7.7.859 · Cited by 1,010
A survey of shape analysis techniques
Loncaric, S. (1998) · Pattern Recognition · doi:10.1016/s0031-2023(97)00122-2 · Cited by 950
Cited by
Cellpose: a generalist algorithm for cellular segmentation
Stringer, C., Wang, T., Michaelos, M., & Pachitariu, M. (2021) · Nature Methods · doi:10.1038/s41592-020-01018-x · Cited by 4,369
Vision‐Based Automated Crack Detection for Bridge Inspection
Yeum, C. M., & Dyke, S. J. (2015) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/mice.12141 · Cited by 517
Yamashita, R., Perrin, T., Chakraborty, J., Chou, J. F., Horvat, N., Koszalka, M. A., Midya, A., Gonen, M., Allen, P., Jarnagin, W. R., et al. (2020) · European Radiology · doi:10.1007/s00330-019-06381-8 · Cited by 76
Metadata
- Authors
- Mingqiang, Y., Kidiyo, K., & Joseph, R.
- Venue
- Pattern Recognition Techniques, Technology and Applications
- Publisher
- InTech
- Published
- 2008-11-01
- DOI
- 10.5772/6237
- OpenAlex
- W1570052007
- Cited by
- 674
- References
- 35
- FWCI
- 12.87
- Type
- book chapter
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Survey of Shape Feature Extraction Techniques. https://app.cochat.ai/papers/10.5772/6237
- The paper
- Mingqiang, Y., Kidiyo, K., & Joseph, R. (2008). A Survey of Shape Feature Extraction Techniques. Pattern Recognition Techniques, Technology and Applications. https://doi.org/10.5772/6237
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.