There are two partition methods for image level parallelism. The first one is a static partition, which groups the images statically. The other is a dynamical ...
In this paper, we first analyze the parallelism constraints in the algorithms, such as imbalanced workloads and indeterminate time distributions. Based on such ...
Mar 10, 2016 · Currently, multimedia data has become one of the most important data types processed and transferred over the Internet. To extract useful ...
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To extract useful information from a huge amount of such data, SIFT and SURF, as two most popular image feature extraction algorithms, have been widely used in ...
In this paper, we study the cubic convolution interpolation algorithm for image processing. We shall parallelize the algorithm using the parallel programming ...
Missing: feature extraction
Bibliographic details on Parallelizing image feature extraction algorithms on multi-core platforms.
Image/video feature extraction parallel algorithm based on multi-core ...
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The image/video feature extraction parallel algorithm combines the task level parallel technology with the pipeline level parallel technology to realize feature ...
In this paper, we study the cubic convolution interpolation algorithm for image processing. We shall parallelize the algorithm using the parallel programming ...
Analyze the multi-core scheduling characteristics to ensure the real-time processing and test the system's performance based on related algorithm. Published ...
Missing: feature extraction
This paper solves some face recognition problems including segmenting, extracting and identifying facial features that are thought to face from the background.