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Recently, the combination of move-to-front transform and adaptive run-length encoding accomplished efficient compression of the popular chain codes. [14] Chain codes also can be used to obtain high levels of compression for image documents, outperforming standards such as DjVu and JBIG2.
According to a classification proposed by Fuggetta, Picco and Vigna, [1] code mobility can be either strong or weak: strong code mobility involves moving both the code, data and the execution state from one host to another, notably via a process image (this is important in cases where the running application needs to maintain its state as it ...
An image sometimes includes a familiar object to communicate scale. Such fiducial markers should be as culturally universal and standardized as possible: rulers, matches, batteries, pens/pencils, footballs (soccer balls), people and their body parts, vehicles, and famous structures such as the Eiffel Tower are good choices, but many others are possible.
Image registration or image alignment algorithms can be classified into intensity-based and feature-based. [3] One of the images is referred to as the moving or source and the others are referred to as the target, fixed or sensed images. Image registration involves spatially transforming the source/moving image(s) to align with the target image.
Scale the image to be no greater than the given width or height, keeping its aspect ratio. Scaling up (i.e. stretching the image to a greater size) is disabled when the image is framed. Link Link the image to a different resource, or to nothing. Alt Specify the alt text for the image. This is intended for visually impaired readers.
Billboards and other electronic signs use apparent motion to simulate moving text by flashing lights on and off as if the text is moving.. The term illusory motion, or motion illusion or apparent motion, refers to any optical illusion in which a static image appears to be moving due to the cognitive effects of interacting color contrasts, object shapes, and position. [1]
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Block Truncation Coding (BTC) is a type of lossy image compression technique for greyscale images. It divides the original images into blocks and then uses a quantizer to reduce the number of grey levels in each block whilst maintaining the same mean and standard deviation.