A new method for robust feature extraction of otolith growth marks using fingerprint recognition methods

2005 ◽  
Vol 56 (5) ◽  
pp. 791 ◽  
Author(s):  
M. Palmer ◽  
A. Álvarez ◽  
J. Tomás ◽  
B. Morales-Nin
Keyword(s):  
Image Analysis ◽  
Feature Extraction ◽  
Age Determination ◽  
Fingerprint Recognition ◽  
New Method ◽  
Otolith Growth ◽  
Contour Analysis ◽  
Recent Developments ◽  
Robust Feature Extraction ◽  
Essential Knowledge

Individual and population age structures constitute essential knowledge for proper management of commercial fisheries. Despite the important advances made in age determination using otolith growth structures, there is still a need to improve both precision and accuracy. The problem of increasing precision in age estimations has been addressed via increasing automation in the identification of growth marks. However, approaches based on otolith size, weight, perimeter, and related measurements (including contour analysis) have moderate success in age prediction. Likewise, early attempts of image analysis have reported poor results, both in cases of 1D (grey-intensity profiles) or 2D images. Recent developments in image analysis have broken this trend, and fully automatic techniques could be an alternative for routine ageing in the near future. Here, we propose a new method for 2D feature extraction that provides robust numerical descriptors of the growth structures of otoliths.

Recent developments in automated Transmission Electron MI

1989 ◽  
Vol 47 ◽  
pp. 46-47
Author(s):  
W.J. de Ruijter ◽  
P. Rez ◽  
David J. Smith
Keyword(s):  
Image Analysis ◽  
Computer Image ◽  
Lens Design ◽  
Computer Image Analysis ◽  
Transmission Electron ◽  
Resolution Electron ◽  
Recent Developments ◽  
On Line ◽  
Routine Procedures ◽  
Near Future

There is growing interest in the on-line use of computers in high-resolution electron n which should reduce the demands on highly skilled operators and thereby extend the r of the technique. An on-line computer could obviously perform routine procedures hand, or else facilitate automation of various restoration, reconstruction and enhan These techniques are slow and cumbersome at present because of the need for cai micrographs and off-line processing. In low resolution microscopy (most biologic; primary incentive for automation and computer image analysis is to create a instrument, with standard programmed procedures. In HREM (materials researc computer image analysis should lead to better utilization of the microscope. Instru (improved lens design and higher accelerating voltages) have improved the interpretab the level of atomic dimensions (approximately 1.6 Å) and instrumental resolutior should become feasible in the near future.

A Review on Feature Extraction Methods for Image Analysis

2020 ◽  
Author(s):  
Vricha Chavan ◽  
​Jimit Shah ◽  
Mrugank Vora ◽  
Mrudula Vora ◽  
Shubhashini Verma
Keyword(s):  
Image Analysis ◽  
Feature Extraction ◽  
Extraction Methods

scholarly journals A Feature Set for Cytometry on Digitized Microscopic Images

2003 ◽  
Vol 25 (1) ◽  
pp. 1-36 ◽  
Author(s):  
Karsten Rodenacker ◽  
Ewert Bengtsson
Keyword(s):  
Image Analysis ◽  
Feature Extraction ◽  
Systematic Approach ◽  
Structural Features ◽  
Biomedical Image Analysis ◽  
Feature Sets ◽  
Biomedical Image ◽  
Rules Of Thumb ◽  
Quantitative Cytology ◽  
The Eu

Feature extraction is a crucial step in most cytometry studies. In this paper a systematic approach to feature extraction is presented. The feature sets that have been developed and used for quantitative cytology at the Laboratory for Biomedical Image Analysis of the GSF as well as at the Center for Image Analysis in Uppsala over the last 25 years are described and illustrated. The feature sets described are divided into morphometric, densitometric, textural and structural features. The latter group is used to describe the eu‐ and hetero‐chromatin in a way complementing the textural methods. The main goal of the paper is to bring attention to the need of a common and well defined description of features used in cyto‐ and histometrical studies. The application of the sets of features is shown in an overview of projects from different fields. Finally some rules of thumb for the design of studies in this field are proposed. Colour figures can be viewed onhttp://www.esacp.org/acp/2003/25‐1/rodenacker.htm.

Age determination and growth of orange roughy (Hoplostethus atlanticus): a comparison of annulus counts with radiometric ageing

1995 ◽  
Vol 52 (2) ◽  
pp. 391-401 ◽  
Author(s):  
David C. Smith ◽  
Simon G. Robertson ◽  
Gwen E. Fenton ◽  
Stephen A. Short
Keyword(s):  
Age Determination ◽  
Percentage Reduction ◽  
Age At Maturity ◽  
Otolith Growth ◽  
Two Stage ◽  
Orange Roughy ◽  
Mass Growth ◽  
Hoplostethus Atlanticus ◽  
Age Estimates ◽  
Radiometric Data

Ages of orange roughy (Hoplostethus atlanticus) determined by two methods (counting annuli on the surface of whole and in longitudinally sectioned otoliths) were similar up to maturity. Beyond maturity, age estimates from sectioned otoliths exceeded those from whole otoliths. Maximum recorded age was 125 years for an individual 41 cm standard length (SL), and age at maturity was estimated to be 25 years (30–32 cm SL). These are consistent with ages estimated previously by radiometric methods. Results demonstrated a two-stage linear relationship between otolith weight and age that confirmed the two-stage otolith mass growth model previously used in radiometric ageing. However, in the radiometric analyses the reduction in otolith growth was arbitrarily estimated at 45% of the immature rate whereas annuli data demonstrated a reduction after maturity to 62% of the immature rate. The new estimates of otolith mass growth rate were incorporated into the radiometric data and ages recalculated, which reduced age estimates for 38–40 cm SL fish from 77–149 to 59–101 years. The radiometric data were also recalculated using only the percentage reduction in otolith growth after maturity, giving the radiometric age of 125 ± 9 years for the oldest fish.

scholarly journals Digital Imaging as a Possible Approach in Evaluation of Islet Yield

2003 ◽  
Vol 12 (2) ◽  
pp. 129-133 ◽  
Author(s):  
Peter Girman ◽  
Jan Kříž ◽  
Jozef Friedmanský ◽  
FrantišEk Saudek
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Imaging ◽  
Digital Image Analysis ◽  
Three Dimensional ◽  
Two Dimensions ◽  
New Method ◽  
Important Method ◽  
Three Dimensional Objects ◽  
Significant Difference

Digital image analysis (DIA) is a new method in assessment of islet amount, which is expected to provide reliable and consistent results. We compared this method with conventional counting of small numbers of rat islets. Islets were isolated from 8 pancreases and counted in 24 samples in duplicate, first routinely by sizing according to estimated diameters under a calibrated reticule and then by processing of islets pictures taken by camera. As presumed, no significant difference was found in absolute numbers of islets per sample between DIA and conventional assessment. Volumes of islets per sample measured by DIA were on average more than 10% higher than amounts evaluated conventionally, which was statistically significant. DIA has been shown to be an important method to remove operator bias and provide consistent results. Evaluation of only two dimensions of three-dimensional objects still represents a certain limitation of this technique. With lowering of computer prices the system could become easily available for islet laboratories.

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