Decision support system for classifying archaeological pottery profiles based on Mathematical Morphology

Lucena, Manuel; Martínez-Carrillo, A. L.; Fuertes, José Manuel; Carrascosa, Francisco Javier; Ruiz, Arturo

doi:10.1007/s11042-014-2063-6

Cited by 13 publications

(6 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors used the fragments excavated from the Independence National Historical Park (INHP) in Philadelphia, Pennsylvania. Lucena et al (2016) proposed a new method based on morphological data to help the archaeologist for profile classification. In this way, the authors proposed a decision support system by encoding morphological data on potteries profiles.…”

Section: Performed Studies From 2010 To 2019mentioning

confidence: 99%

“…These features are categorized in Figure 4: the most commonly used features are the rotational axis and geometric, profile, and color ones (Belenguer & Vidal, 2012;Karasik & Smilansky, 2011;Rasheed & Nordin, 2015). However, in recent years, more attention has been paid to morphological features, which are more difficult to recognize, being asymmetric structures, but are semantically significant and have specific geometric features useful to drive the assembling process (Di Kalasarinis & Koutsoudis, 2019;Lucena et al, 2016).…”

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

“…The comparison and classification of objects are one of the most important tasks for an archaeologist. Therefore, it would be interesting to provide automated methods to assist them in the classification process (Lucena et al, 2016). Regarding the classification step, the published methods can be classified as supervised and unsupervised.…”

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

See 2 more Smart Citations

Review of computer-based methods for archaeological ceramic sherds reconstruction

Eslami

Angelo

Stefano

et al. 2020

Virtual archaeol. rev.

View full text Add to dashboard Cite

Potteries are the most numerous finds found in archaeological excavations; they are often used to get information about the history, economy, and art of a site. Archaeologists rarely find complete vases but, generally, damaged and in fragments, often mixed with other pottery groups. By using the traditional manual method, the analysis and reconstruction of sherds are performed by a skilled operator. Reviewed papers provided evidence that the traditional method is not reproducible, not repeatable, time-consuming and its results have great uncertainties. To overcome the aforementioned limits, in the last years, researchers have made efforts to develop computer-based methods for archaeological ceramic sherds analysis, aimed at their reconstruction. To contribute to this field of study, in this paper, a comprehensive analysis of the most important available publications until the end of 2019 is presented. This study, focused on pottery fragments only, is performed by collecting papers in English by the Scopus database using the following keywords: “computer methods in archaeology", "3D archaeology", "3D reconstruction", "automatic feature recognition and reconstruction", "restoration of pottery shape relics”. The list is completed by additional references found through the reading of selected papers. The 53 selected papers are divided into three periods of time. According to a detailed review of the performed studies, the key elements of each analyzed method are listed based on data acquisition tools, features extracted, classification processes, and matching techniques. Finally, to overcome the actual gaps some recommendations for future researches are proposed.Highlights:<ul><li>The traditional manual method for reassembling sherds is very time-consuming and costly; it also requires a great deal effort from skilled archaeologists in repetitive and routine activities.</li><li>Computer-based methods for archaeological ceramic sherds reconstruction can help archaeologists in the above-mentioned repetitive and routine activities.</li><li>In this paper, the state-of-the-art computer-based methods for archaeological ceramic sherds reconstruction are reviewed, and some recommendations for future researches are proposed.</li></ul>

show abstract

Section: Performed Studies From 2010 To 2019mentioning

confidence: 99%

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

See 1 more Smart Citation

Review of computer-based methods for archaeological ceramic sherds reconstruction

Eslami

Angelo

Stefano

et al. 2020

Virtual archaeol. rev.

View full text Add to dashboard Cite

show abstract

“…Morphology [1] is a non-linear image processing theory based on a set theory which is founded by the French mathematician J. Serra and G. Matheron in 1964. Morphology is based on complete lattices theory [2] to study the shape and the structure of image (or signal), which is widely used in computer vision, pattern recognition, signal processing and image analysis, calculation methods and data processing and so on [3][4][5][6][7][8][9]. At present, the mathematical morphology theories on binary images and greyscale images are very perfect, but on colour images are still not ideal.…”

Section: Introductionmentioning

confidence: 99%

New colour morphological operators on hypergraph

Wang

Liang

et al. 2018

IET Image Processing

View full text Add to dashboard Cite

“…Mathematical morphology (MM) is established as a powerful tool in image processing tasks especially for texture analysis and segmentation of distorted images [15,25,27]. Moreover, the application of fuzzy logic in noise rectification is also gaining more attraction [16,22].…”

Section: Introductionmentioning

confidence: 99%

Modified particle swarm optimization and fuzzy regularization for pseudo de-convolution of spatially variant blurs

Bilal

Mujtaba

Jaffar

2015

Multimed Tools Appl

View full text Add to dashboard Cite

We propose a modified particle swarm optimization (MPSO) based method for Pseudo De-convolution of the ill-posed inverse problem namely, the space-variant image degradation (SVD). In this paper, SVD is simulated by the pseudo convolution of different sub-regions of the image with different known blurring kernels and additive random noise with unknown variance. Two heuristic modifications are proposed in PSO: 1) Initialization of the swarm and 2) Mutation of the global best. Fuzzy logic is applied for the computation of regularization parameter (RP) to cater for the sensitivity of the problem. The computation of RP is crucial due to the additive noise in the SVD image. Thus mathematical morphology (MM) is applied for better extraction of spatial activity from the distorted image. The performance of the proposed method is evaluated with different test images and noise powers. Comparative analysis demonstrates the superiority of proposed restoration, in terms of quantitative measures, over well-known existing and state-of-the-art SVD approaches.

show abstract

Decision support system for classifying archaeological pottery profiles based on Mathematical Morphology

Cited by 13 publications

References 18 publications

Review of computer-based methods for archaeological ceramic sherds reconstruction

Review of computer-based methods for archaeological ceramic sherds reconstruction

New colour morphological operators on hypergraph

Modified particle swarm optimization and fuzzy regularization for pseudo de-convolution of spatially variant blurs

Contact Info

Product

Resources

About