KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Settings

Access type: UnknownSubject: search.filters.subject.Fractal dimension

Search Results

Now showing 1 - 3 of 3
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Use of digital image analysis as a monitoring tool for non-uniform deformation of shrinkable materials during drying
    (2017-01-01)
    Jinorose, Maturada
    ;
    Stienkijumpai, Anyanun
    ;
    Devahastin, Sakamon
    Deformation is a phenomenon that is common during drying. Generally, deformation is evaluated and reported in terms of volumetric shrinkage. However, volumetric shrinkage cannot be used to describe non-uniform deformation, which commonly takes place during drying of shrinkable materials such as biopolymers, fruits and vegetables. In the present study, algorithms and software were developed to first reconstruct 3D images from 2D images, and then to monitor non-uniform deformation of such images. Agar gel with different sugar contents were used as the test materials and were allowed to undergo drying at different rates. The developed image reconstruction algorithms were successfully validated with standard geometrical shapes. Various image-based parameters, both in two dimensions, i.e. projected area, perimeter, major axis length, minor axis length, equivalent diameter, extent and fractal dimension; and in three dimensions, i.e. volume, sphericity, Wadell's sphericity, Wadell's roundness, radius ratio and Hoffmann shape entropy, were then calculated. The results showed that extent and fractal dimension could be used to identify the onset and to monitor non-uniform deformation in two dimensions, while sphericity could be used for such tasks in three dimensions.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Improved triangle box-counting method for fractal dimension estimation
    (2015-01-01)
    Kaewaramsri, Yothin
    ;
    Woraratpanya, Kuntpong
    A fractal dimension (FD) is an effective feature, which characterizes roughness and self-similarity of complex objects. However, the FD in nature scene requires the effective method for estimation. The existing methods focus on the improvement of selecting the suitable height of box-counts. This cannot overcome the overcounting problem, which is a key factor to have an impact on the accuracy of the FD estimation. This paper proposes a more accurate FD estimation, an improved triangle box-counting method, to increase the precision of box-counts associated with box sizes. The triangle-box-partition technique provides the double precision for box-counts, thus it can solve the overcounting issue and enhance the accuracy of the FD estimation. The proposed method is evaluated its performance in terms of fitting error. The experimental results show that the proposed method outperforms the existing methods, including differential box-counting (DBC), improved DBC (IDBC), and box-counting with adaptable box height (ADBC) methods.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    A novel image-analysis based approach to evaluate some physicochemical and cooking properties of rice kernels
    (2014-01-01)
    Jinorose, Maturada
    ;
    Prachayawarakorn, Somkiat
    ;
    Soponronnarit, Somchart
    Prior to being edible, paddy needs to undergo several processing steps, which inevitably affect the kernel quality, both in terms of the physical, physicochemical and cooking characteristics. Unfortunately, many of the kernel quality parameters are time-consuming and not straightforward to evaluate, rendering the control of the paddy processing quite ineffective. An alternative means, which allows rapid determination of various properties of the kernels are therefore desirable. This study represents the first attempt to correlate image-analysis based apparent characteristics of rice kernels to physicochemical as well as cooking properties of the kernels for effective monitoring of rice processing and cooking processes. Parboiled rice production process was selected as a test process. Image-analysis based results, in terms of the changes of the kernel dimensions (i.e.; elongation ratio, width ratio, and swelling) and translucency as well as the fractal dimension of the kernel images, were noted to adequately correlate with the tested physicochemical (i.e.; amylose content, water uptake, degree of parboiling, which is closely related to the degree of starch gelatinization) as well as cooking (i.e.; texture and cooked level of rice kernels) properties of the rice kernels of two varieties of Thai rice. This represents an attractive evaluation technique that can be adopted by an industry for various properties measurement and quality control. © 2013 Elsevier Ltd. All rights reserved.