Color Thresholding
Color Thresholding - Related Videos
09:20
Color Afterimages
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University Human color vision is impressive. People with normal color vision can tell apart millions of individual hues. Most amazingly, this ability is achieved with fairly simple hardware. Part of the power of human color vision comes from a clever bit of engineering in the human brain. There, color perception relies on what is known as an 'opponent system.' This means that the presence of one kind of stimulus is treated as evidence for...
03:02
Colors and Magnetism
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2020
Color in Coordination Complexes When atoms or molecules absorb light at the proper frequency, their electrons are excited to higher-energy orbitals. For many main group atoms and molecules, the absorbed photons are in the ultraviolet range of the electromagnetic spectrum, which cannot be detected by the human eye. For coordination compounds, the energy difference between the d orbitals often allows photons in the visible range to be absorbed and emitted, which is seen as colors by the human eye.
06:48
The Staircase Procedure for Finding a Perceptual Threshold
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University Psychophysics is the name for a set of methods in perceptual psychology designed in order to relate the actual intensity of stimuli to their perceptual intensity. One important aspect of psychophysics involves the measurement of perceptual thresholds: How bright does a light need to be for a person to be able to detect it? How little pressure applied to the skin is detectable? How soft can a sound be and still be heard? Put...
10:27
Training Synesthetic Letter-color Associations by Reading in Color
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Cited by 5 •
2014
Reading in color is a new method for training letter-color associations that are typically found only in grapheme-color synesthetes. It involves an implicit form of training that has potential for long-term associative training methods because the training is a byproduct of reading and any text can be colored.
05:45
Rapid Determination of the Thermal Nociceptive Threshold in Diabetic Rats
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Cited by 10 •
2012
Here, we describe a rapid reliable and simple procedure to determine the lowest temperature at which rats or mice show nocifensive behavior, i.e. the thermal nociceptive threshold (TNT). This method applies a slowly increasing thermal stimulus allowing precise and reproducible estimation of TNTs with minimum, if any, stress to the animals.
FAQs
The method evaluates pixel values in selected color channels and compares them with specified threshold ranges. A pixel is retained when it satisfies the chosen color criteria and excluded when it does not. This channel-based decision allows analysis to focus on visual signals associated with stained cells, fluorescent structures, tissue regions, colonies, or anatomical features.
RGB and HSV provide different ways to describe the same image colors. RGB separates red, green, and blue channel values, whereas HSV represents hue, saturation, and value. Choosing between them changes how threshold criteria are expressed. The appropriate representation depends on which color characteristics best distinguish the biological feature from the surrounding image.
Threshold values determine which pixels satisfy the selection criteria, so changing them can alter the included region and the excluded background. Thresholds may be defined by the user or determined computationally. Consistent criteria are important because the resulting mask directly affects measurements of area, intensity, shape, and abundance.
A binary mask converts the color-based selection into a form that separates included pixels from excluded pixels. This provides a basis for measuring the selected feature rather than evaluating the entire image indiscriminately. In biological research, the mask can support quantitative comparisons of region size, signal intensity, shape, or feature abundance.
Begin with an image containing the feature of interest, choose relevant color channels such as RGB or HSV, and define thresholds manually or computationally. Apply those criteria to assign pixels to the selected or excluded class, producing a binary mask. The mask can then be used for measurements and subsequent image-based comparisons.
It is useful when a biological feature has a distinguishable color signal within a more complex image. Applications described for this approach include isolating stained cells, fluorescent structures, tissue regions, colonies, and anatomical features. By converting these visual signals into measurable regions, the technique supports quantitative analysis in both microscopy and photography.