scholarly journals Image complexity determines degree of viewpoint dependence

2010 ◽  
Vol 2 (7) ◽  
pp. 48-48
Author(s):  
A. Cate ◽  
M. Behrmann
Keyword(s):  
Image Complexity ◽  
Viewpoint Dependence

scholarly journals Preparatory Experiments Regarding Human Brain Perception and Reasoning of Image Complexity for Synthetic Color Fractal and Natural Texture Images via EEG

2020 ◽  
Vol 11 (1) ◽  
pp. 164
Author(s):  
Irina E. Nicolae ◽  
Mihai Ivanovici
Keyword(s):  
Human Perception ◽  
Event Related Potentials ◽  
Classification Performance ◽  
Subjective Perception ◽  
Image Perception ◽  
Image Complexity ◽  
Temporal Area ◽  
Practical Applications ◽  
Related Potentials ◽  
Texture Complexity

Texture plays an important role in computer vision in expressing the characteristics of a surface. Texture complexity evaluation is important for relying not only on the mathematical properties of the digital image, but also on human perception. Human subjective perception verbally expressed is relative in time, since it can be influenced by a variety of internal or external factors, such as: Mood, tiredness, stress, noise surroundings, and so on, while closely capturing the thought processes would be more straightforward to human reasoning and perception. With the long-term goal of designing more reliable measures of perception which relate to the internal human neural processes taking place when an image is perceived, we firstly performed an electroencephalography experiment with eight healthy participants during color textural perception of natural and fractal images followed by reasoning on their complexity degree, against single color reference images. Aiming at more practical applications for easy use, we tested this entire setting with a WiFi 6 channels electroencephalography (EEG) system. The EEG responses are investigated in the temporal, spectral and spatial domains in order to assess human texture complexity perception, in comparison with both textural types. As an objective reference, the properties of the color textural images are expressed by two common image complexity metrics: Color entropy and color fractal dimension. We observed in the temporal domain, higher Event Related Potentials (ERPs) for fractal image perception, followed by the natural and one color images perception. We report good discriminations between perceptions in the parietal area over time and differences in the temporal area regarding the frequency domain, having good classification performance.

Research on the image complexity based on texture features

2015 ◽  
Vol 8 (3) ◽  
pp. 407-414 ◽  
Author(s):  
陈燕芹 CHEN Yan-qin ◽  
段锦 DUAN Jin ◽  
祝勇 ZHU Yong ◽  
钱小飞 QIAN Xiao-fei ◽  
肖博 XIAO Bo
Keyword(s):  
Texture Features ◽  
Image Complexity

scholarly journals Image complexity and feature mining for steganalysis of least significant bit matching steganography

2008 ◽  
Vol 178 (1) ◽  
pp. 21-36 ◽  
Author(s):  
Qingzhong Liu ◽  
Andrew H. Sung ◽  
Bernardete Ribeiro ◽  
Mingzhen Wei ◽  
Zhongxue Chen ◽  
...  
Keyword(s):  
Least Significant Bit ◽  
Image Complexity ◽  
Feature Mining
Sign in / Sign up

Export Citation Format

Share Document