Lack of Standards for the Size of Figures Compared to Letters
– leads to inconsistency across different vision tests and manufacturers.
- It is an obvious task for ophthalmological organizations and research institutions to examine widespread symbol optotypes and measure credible compensation factors. By following a more calibrated and standardized approach, it can be ensured that vision tests with symbols provide comparable and reliable results.
- The lack of research-based standards for the weighting between symbol-based and letter-based optotypes leads to inconsistent and often overly favorable compensations.
- Manufacturers choose to oversize symbols to be on the safe side and ensure that test subjects can see them clearly.
- However, the symbols are often too large compared to what is cognitively necessary. This can lead to vision tests underestimating the degree of visual problems. Test subjects may achieve better results than their actual vision level warrants.
Empirical Studies and Research Form the Basis for Standardized Weighting Factors
- To determine whether symbols are oversized, it is important to conduct empirical studies comparing performance on vision tests with symbols versus letters. These empirical studies form the basis for the necessary precise calibration of the figures’ size relative to children’s ability to recognize them. This is crucial for ensuring fair and accurate test results.
- Based on these empirical studies and research, standards should be developed for the weighting factors that respective symbol-based optotype sets can and should be regulated by to provide comparable vision test results.
- Keep the difficulty level as consistent as possible within each optotype set.
- One should avoid figures in an optotype set varying too much in their design and complexity, as this makes it difficult to establish a common standard compensation factor.
- Manufacturers should always conduct critical evaluations of their optotypes through empirical studies to ensure that each symbol does not have a significantly different cognitive difficulty level compared to the other optotypes in the set.
In general, symbols that are all equally familiar and simple should be used to reduce cognitive load and minimize the degree of enlargement. It is also preferable to choose symbols that, in their design and complexity, resemble letters as much as possible. Letters achieve their recognizability through the fact that they have extremities, i.e., they stick out in a noticeable way. Letters such as K, H, V, and T are good examples. If easily recognizable symbols are produced with these letter forms in mind, the need to oversize the symbols to compensate for cognitive complexity is reduced, as extremities on symbols bring them cognitively closer to letter-based optotypes.
Line Thickness, etc.
- If compensation weightings are correctly performed to even out cognitive differences, it is no longer crucial whether the line thickness used on symbols corresponds to the line thickness on letters.
- Ensure that figures have high contrast against the background, just as letters usually do. Figures with lower contrast may require larger sizes to achieve the same visibility as letters.
- Symbols with less complex shapes can more easily be compared to letters. More complex symbols must be enlarged more than simple figures to achieve the same level of recognizability.
- Test figures and letters in a controlled experimental setup to calibrate the sizes. This involves having test subjects undergo vision tests with both symbols and letters and adjusting the sizes until the results are comparable.
- Use statistical analyses to determine the optimal sizes for figures relative to letters based on the test results.
ISOeyes has conducted extensive empirical studies and subsequently performed calibrations of all our self-developed Optotypes – ensuring that they provide identical vision test results!
Differences in Perception of Letters Versus Figures
Scientific research in visual perception and cognitive psychology has examined the differences in the perception of letters versus figures. The science indicates that letters are generally cognitively easier for the eye and brain to identify compared to figures, due to a higher degree of familiarity, specialized brain areas, and their designed distinctiveness. This makes letters an effective tool in many visual tasks, although figures also have their place, especially when working with non-literate individuals or specific visual tests:
Familiarity and Experience
- Letters: Literate individuals have extensive experience recognizing letters, as they constantly interact with them in daily life. This higher degree of familiarity makes it cognitively easier for the eye and brain to identify letters quickly and accurately.
- Figures: Figures can vary more in complexity and form than letters. While simple figures (such as circles, squares, and hearts) may be easy to recognize, more complex or unfamiliar figures may require more cognitive processing.
Cognitive Processes
- Letters: The recognition of letters involves specialized areas in the brain, such as the visual word form area (VWFA), which is responsible for processing written words and letters. This specialization makes letter recognition highly efficient.
- Figures: The recognition of figures involves several different areas of the brain, depending on the complexity and significance of the figure. This can make the process more cognitively demanding compared to letters.
Visual Disambiguation
- Letters: Most letters are designed to be visually distinct, even when closely packed together, which aids in quick recognition.
- Figures: Figures can vary more in shape and size, making it harder to distinguish between them, especially if they are complex or unfamiliar.
Contrast and Form
- Letters: Often have strong contrasts and well-defined shapes, making them easy to see and recognize, even in low resolution or from a distance.
- Figures: Depending on their design, figures may vary more in contrast and form, which can affect visibility and recognition.
Empirical Studies
- Studies on Word Recognition: Many studies have shown that people can recognize words and letters extremely quickly (within a few milliseconds), suggesting a high degree of automation in this process.
- Studies on Figure Recognition: Recognizing figures, especially unfamiliar or complex figures, can take longer and require more cognitive processing.
Practical Implications
- Vision Tests: Vision tests that use letters can benefit from people’s familiarity with these symbols and thus provide more consistent results. Tests with figures can be useful for testing vision in people who cannot read (such as young children) but may vary more depending on the design of the figure.
- Design of Visual Materials: When designing visual materials for quick recognition (such as signs, warnings, etc.), it may be more effective to use letters or very simple figures to ensure quick and accurate perception.
Comparison of Two Drawings of an Apple:
- Drawing 1:
- Square of 5×5 cm
- Line thickness of 0.8 cm
- Drawing 2:
- Square of 10×10 cm
- Line thickness of 0.4 cm
Conclusions on Visual Perception and Recognition:
- Size and Scale:
- A- Larger images provide more visual information and detail, making them easier to recognize.
- B- Larger drawings project larger images on the retina, facilitating visual sharpness and object recognition.
- Line Thickness:
- Thicker lines can increase contrast and make contours more distinct, but the size of the image plays a more significant role in overall recognition.
- Improved Recognition at Different Distances:
- Larger drawings are easier to see and recognize from greater distances, even if the line is thinner.
- Contrast and Visibility:
- Even if the line is thinner, the contrast between the line and the background may still be sufficient to make the shape easily recognizable in larger drawings.
- Visual Physiology:
- Human visual acuity is better suited to seeing objects of medium to large size.
References:
- Regarding point 1A: Goldstein, E. B. (2013). Sensation and Perception (9th ed.). Cengage Learning. Chapter 5, pages 100-135.
- Regarding point 1B: Pelli, D. G., Robson, J. G., & Wilkins, A. J. (1988). The Design of a New Letter Chart for Measuring Contrast Sensitivity. Clinical Vision Sciences, 2(3), 187-199.
- Regarding point 2: Wang, K., & Cottrell, G. W. (2012). The Strengths and Weaknesses of the Stroke Width Transform for Text Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(6), 1173-1186.
- Regarding point 3: Hecht, S., Shlaer, S., & Pirenne, M. H. (1942). Energy, Quanta, and Vision. The Journal of General Physiology, 25(6), 819-840.
- Regarding point 4: Kandel, E. R., Schwartz, J. H., & Jessell, T. M. (2000). Principles of Neural Science (4th ed.). McGraw-Hill. Chapter 27, pages 492-525.
- Regarding point 5: Duin, R. P. W., & Pavešić, N. (2001). Visual Pattern Recognition in Machine Vision. Pattern Recognition, 34(11), 2213-2226.