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Macro photography may also be accomplished by mounting a lens in reverse, in front of a normally mounted lens of greater focal length, using a macro coupler which screws into the front filter threads of both lenses. This method allows most cameras to maintain the full function of electronic and mechanical communication with the normally mounted ...
An image macro is a piece of digital media featuring a picture, or artwork, with some form of text superimposed. The text frequently appears at the top and bottom of ...
A gigapixel macro image is a digital image bitmap composed of one billion (10 9) pixels (picture elements), or 1000 times the information captured by a 1 megapixel digital camera. Creating such high-resolution images involves making mosaics ( image stitching ) of a large number of high-resolution digital photographs which are then combined into ...
In addition to working with HTML pages, the commercial editions could automate Adobe Flash, Adobe Flex, Silverlight, and Java applets by using Directscreen and image recognition technology. The freeware version of iMacros contained no control flow statements and, with a few minor exceptions, [ 18 ] complex or conditional code required scripting ...
Connected-component labeling is used in computer vision to detect connected regions in binary digital images, although color images and data with higher dimensionality can also be processed. [1] [2] When integrated into an image recognition system or human-computer interaction interface, connected component labeling can operate on a variety of ...
The workflow could include ImageJ macro; CVIPtools A complete open-source GUI-based Computer Vision and Image Processing software, with C functions libraries COM based dll along with two utilities program for algorithm development and batch processing. Fiji (software), an image processing package based on ImageJ
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.
In the detection phase of the Viola–Jones object detection framework, a window of the target size is moved over the input image, and for each subsection of the image the Haar-like feature is calculated. This difference is then compared to a learned threshold that separates non-objects from objects.