Related Experiment Video
Updated: Sep 26, 2025
11:15
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
Published on: June 27, 2013
33.9K
Comparison of three image-analysis-based visual texture calculation methods: energy, entropy, and texture change
Murat O Balaban1, Bahar Gümüş2, Erkan Gümüş3
1Chemical and Materials Engineering Department, University of Auckland, Auckland, New Zealand.
Journal of the Science of Food and Agriculture
|April 21, 2022
Summary
Texture analysis methods were tested for rotation invariance. The texture change index (TCI) proved more precise than energy and entropy for distinguishing texture levels, showing minimal variation with image rotation.
Area of Science:
- Image analysis
- Texture analysis
- Computer vision
Background:
- Evaluated three image analysis methods for visual texture measurement.
- Tested methods on images with high (scaled carp) and low (mirror carp) texture.
- Assessed the impact of image rotation (0-90°) on texture measurements.
Purpose of the Study:
- To compare the rotation invariance of different image texture analysis methods.
- To determine the precision of texture analysis methods in distinguishing between varying texture levels.
- To identify the most reliable method for texture quantification under rotational transformations.
Main Methods:
- Applied image histogram analysis to calculate energy (E) and entropy (H).
- Utilized co-occurrence matrices with varying step sizes (d) and angles (θ).
- Calculated texture change index (TCI) using 'texture primitives' method.
Main Results:
- Image rotation did not affect histogram-based energy (E) and entropy (H).
- Co-occurrence matrices showed E decreased and H increased with step size (d); averaging over angles (θ) achieved rotation invariance.
- Texture change index (TCI) exhibited negligible variation with rotation, with a significant increase between low and high texture images (5.3-11) compared to histogram E values (0.0069-0.0081).
Conclusions:
- The texture change index (TCI) is a more precise method for discerning visual texture levels than energy and entropy.
- TCI demonstrates superior performance in differentiating texture variations, even with image rotation.
- The findings suggest TCI as a robust tool for texture analysis in applications sensitive to orientation.
Related Concept Videos
03:00Standard Entropy Change for a Reaction
21.5K
Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
21.5K
01:10Entropy Change in Reversible Processes
2.8K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.8K
01:20Entropy and the Second Law of Thermodynamics
3.3K
The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
The relation between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
3.3K
01:18Entropy
2.9K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
2.9K
02:59Enthalpy
37.9K
Chemists ordinarily use a property known as enthalpy (H) to describe the thermodynamics of chemical and physical processes. Enthalpy is defined as the sum of a system’s internal energy (E) and the mathematical product of its pressure (P) and volume (V):
37.9K
02:46Quantifying Heat
57.0K
Thermal Energy Microscopically, thermal energy is the kinetic energy associated with the random motion of atoms and molecules. Temperature is a quantitative measure of “hot” or “cold”, which depends on the amount of thermal energy. When the atoms and molecules in an object are moving or vibrating quickly, they have a higher average kinetic energy (KE) (or higher thermal energy), and the object is perceived as “hot”, or it is described as being at a...
57.0K