Feature Extraction and Selection in Archaeological Images for Automatic Annotation

被引:3
作者
Ben Salah, Marwa [1 ]
Yengui, Ameni [1 ]
Neji, Mahmoud [1 ]
机构
[1] MIRACL Univ Sfax, Dept Comp Sci, Sfax, Tunisia
关键词
Feature extraction; shape; texture; color; spatial location; contour method based; feature selection; principal component analysis; particle swarm optimization;
D O I
10.1142/S0219467822500061
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In this paper, we present two steps in the process of automatic annotation in archeological images. These steps are feature extraction and feature selection. We focus our research on archeological images which are very much studied in our days. It presents the most important steps in the process of automatic annotation in an image. Feature extraction techniques are applied to get the feature that will be used in classifying and recognizing the images. Also, the selection of characteristics reduces the number of unattractive characteristics. However, we reviewed various images of feature extraction techniques to analyze the archaeological images. Each feature represents one or more feature descriptors in the archeological images. We focus on the descriptor shape of the archaeological objects extraction in the images using contour method-based shape recognition of the monuments. So, the feature selection stage serves to acquire the most interesting characteristics to improve the accuracy of the classification. In the feature selection section, we present a comparative study between feature selection techniques. Then we give our proposal of application of methods of selection of the characteristics of the archaeological images. Finally, we calculate the performance of two steps already mentioned: the extraction of characteristics and the selection of characteristics.
引用
收藏
页数:17
相关论文
共 43 条
  • [1] Albatal R., 2010, Annotation automatiqued'images a base de phases visuelles Thesis Memory
  • [2] Linear feature extraction from point cloud using color information
    Alshawabkeh, Yahya
    [J]. HERITAGE SCIENCE, 2020, 8 (01)
  • [3] Balan S., INT J RES APPL SCI E, V6, P2321
  • [4] Ben Salah M., 2017, 6 INT C SOFTWARE ENG
  • [5] Ben Salah M., INT C BUSINESS INFOR
  • [6] Bins J., PROC 8 IEEE INT C CO
  • [7] Canedo V.B, J INT ARTIF INTELL R
  • [8] Carvalho S.N, 2015, J INT BIOMED SIGNAL
  • [9] A comparative study of image low level feature extraction algorithms
    El-Gayar, M. M.
    Soliman, H.
    meky, N.
    [J]. EGYPTIAN INFORMATICS JOURNAL, 2013, 14 (02) : 175 - 181
  • [10] Robust histogram construction from color invariants for object recognition
    Gevers, T
    Stokman, H
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2004, 26 (01) : 113 - 118