Automatic Recognition of Human Emotions Induced by Visual Contents of Digital Images Based on Color Histogram

Objective: Color matching technique is one of the requirement in clinical dentistry. Using dental shade selection can help the dentist to determine the suitable color for the patients during fabrication of prosthesis. However the lack of dentists’ knowledge in color science due to many kinds of shade guide becomes a problem in the field of dentistry. So color matching technique by using digital images are feasible solution when suitable color features have been properly manipulated.Material and Methods: Separating the color features of digital images into RGB and HSV feature spaces are the first step of this system. Due to many features in this step, it requires some classifier algorithm according to the shade type of teeth. In this paper, we proposed color teeth classification for dental shade selection using DT, NN, and K-nearest neighbors algorithm based on color histogram feature spaces.Results: The result showed that on using the KNN algorithm it achieved 96.67% in learning process and 90% in testing process which had error level (0.183).Conclusion: It proves that our proposed system have high similarity in color matching according to the learning and testing process.

Download Full-text

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

Pattern Recognition Letters ◽

10.1016/j.patrec.2013.03.019 ◽

2013 ◽

Vol 34 (14) ◽

pp. 1719-1724 ◽

Cited By ~ 8

Author(s):

Darío Maravall ◽

Javier de Lope ◽

Juan Pablo Fuentes

Keyword(s):

Digital Images ◽

Learning Automata ◽

Automatic Recognition ◽

Classification Rules ◽

Knowledge Based ◽

Probabilistic Knowledge

Download Full-text

Digital Image Automatic Recognition and Tracking Based on Electronic Derotation Algorithm

Advances in Multimedia ◽

10.1155/2021/6111812 ◽

2021 ◽

Vol 2021 ◽

pp. 1-7

Author(s):

Meirong Gao

Keyword(s):

Image Recognition ◽

Digital Image ◽

Simulation Experiment ◽

Digital Images ◽

Social Economy ◽

Difficult Problem ◽

Automatic Recognition ◽

Continuous Development ◽

Edge Features

With the continuous development of my country’s social economy, the ways to acquire images have become more and more abundant. How to effectively process, manage, and mine images has become a major and difficult problem in research. In view of the difficult problem of image recognition, the electronic derotation algorithm is introduced in this study, by combing and monitoring the edge features, establishing a corresponding sample database, analyzing the edge features of the image, and performing effective and stable tracking, so as to realize the automatic recognition and tracking of the digital image. The simulation experiment results show that the electronic derotation algorithm is effective and can support the automatic recognition and tracking of digital images.

Download Full-text