Processing is an electronic sketchbook for developing ideas. It is a context for learning fundamentals of computer programming within the context of the electronic arts.
From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures.
Image alignment is the process of matching one image called template (let's denote it as T) with another image, I (see the above figure). There are many applications for image alignment, such as tracking objects on video, motion analysis, and many other tasks of computer vision. In 1981, Bruse D. Lucas and Takeo Kanade proposed a new technique that used image intensity gradient information to search for the best match between a template T and another image I. The proposed algorithm has been widely used in the field of computer vision for the last 20 years, and has had many modifications and extensions. One of such modifications is an algorithm proposed by Simon Baker, Frank Dellaert, and Iain Matthews. Their algorithm is much more computationally effective than the original Lucas-Kanade algorithm.
ITK is a powerful open-source toolkit implementing state-of-the-art algorithms in medical image processing and analysis. MATLAB, on the other hand, is well-known for its easy-to-use, powerful prototyping capabilities that significantly improve productivity. With the help of MATITK, biomedical image computing researchers familiar with MATLAB can harness the power of ITK algorithms while avoiding learning C++ and dealing with low-level programming issues.
A. McAndrew, and A. Venables. SIGCSE '05: Proceedings of the 36th SIGCSE technical symposium on Computer science education, page 337--341. New York, NY, USA, ACM, (2005)- Kuvaprosessoinnin osa-alueita opetettiin yläkoululaisille: kvantisointi, kohinanpoisto, yms.
- Oppilaat tyytyväisiä
- Ei syytä miksei voisi opettaa jo ennen undergraduate/post-graduate tasoa.