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Related Concept Videos

Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Contaminants and Errors01:16

Contaminants and Errors

Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...

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Updated: Jun 8, 2026

Live Cell Imaging of F-actin Dynamics via Fluorescent Speckle Microscopy (FSM)
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Systematic and random errors in electronic speckle photography.

M Sjödahl, L R Benckert

    Applied Optics
    |October 14, 2010
    PubMed
    Summary

    Electronic speckle photography accurately measures displacement fields. By sampling at 70% of the Nyquist frequency, researchers minimized systematic and random errors in this technique.

    Area of Science:

    • Optical Measurement Techniques
    • Solid Mechanics
    • Fluid Mechanics

    Background:

    • Electronic speckle photography (ESP) is a valuable tool for measuring in-plane displacement fields.
    • Understanding and quantifying errors in ESP is crucial for accurate measurements.
    • Key error sources include undersampling, illumination divergence, and displacement magnitude.

    Purpose of the Study:

    • To analyze and quantify systematic and random errors in electronic speckle photography.
    • To determine optimal sampling strategies to minimize these errors.
    • To establish conditions for accurate displacement field measurements using ESP.

    Main Methods:

    • Analysis of systematic errors, identifying a drift toward the closest integral pixel value.
    • Measurement of random errors, correlating them with imaging system parameters (e.g., ƒ-number) and speckle decorrelation.

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  • Investigation of the impact of undersampling on measurement accuracy, considering sensor area limitations.

    • Main Results:

    • Systematic errors are introduced by a drift towards integral pixel values.
    • Random errors are primarily influenced by the imaging system's effective ƒ-number and displacement-induced speckle decorrelation.
    • Significant undersampling can be tolerated due to the finite sensor area before systematic errors become substantial.

    Conclusions:

    • Sampling at approximately 70% of the Nyquist frequency effectively avoids systematic errors.
    • This sampling rate also minimizes random errors, leading to highly accurate in-plane displacement measurements.
    • Electronic speckle photography, when optimized, provides a simple, fast, and reliable method for displacement analysis in mechanics.