Search results
Results From The WOW.Com Content Network
One of the simpler ways of increasing the size, replacing every pixel with a number of pixels of the same color. The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest ...
Examining small sets of image features until likelihood of missing object becomes small; For each set of image features, all possible matching sets of model features must be considered. Formula: (1 – W c) k = Z. W = the fraction of image points that are “good” (w ~ m/n) c = the number of correspondences necessary; k = the number of trials
Adaptive scalable texture compression (ASTC) is a lossy block-based texture compression algorithm developed by Jørn Nystad et al. of ARM Ltd. and AMD. [1]Full details of ASTC were first presented publicly at the High Performance Graphics 2012 conference, in a paper by Olson et al. entitled "Adaptive Scalable Texture Compression".
In image processing, bicubic interpolation is often chosen over bilinear or nearest-neighbor interpolation in image resampling, when speed is not an issue. In contrast to bilinear interpolation, which only takes 4 pixels (2×2) into account, bicubic interpolation considers 16 pixels (4×4).
SIFT keypoints of objects are first extracted from a set of reference images [1] and stored in a database. An object is recognized in a new image by individually comparing each feature from the new image to this database and finding candidate matching features based on Euclidean distance of their feature vectors. From the full set of matches ...
A main problem when applying this operator at a single scale, however, is that the operator response is strongly dependent on the relationship between the size of the blob structures in the image domain and the size of the Gaussian kernel used for pre-smoothing.
OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]).
In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.