Interactive Image Segmentation Using Adaptive Constraint Propagation | Matlab IEEE Project

Interactive Image Segmentation Using Adaptive Constraint Propagation | Matlab Image Processing Final Year IEEE project with source code.
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🚀IEEE Base Paper Title: Interactive Image Segmentation Using Adaptive Constraint Propagation.
💡Implementation Code: MATLAB.
🛠️Tool details: MATLABR2013A.
💰Cost (In Indian Rupees): Rs.3000/

📘IEEE Base paper Abstract:
In this paper, we propose interactive image segmentation using adaptive constraint propagation (ACP), called ACP Cut. In interactive image segmentation, the interactive inputs provided by users play an important role in guiding image segmentation. However, these simple inputs often cause bias that leads to failure in preserving object boundaries. To effectively use this limited interactive information, we employ ACP for semi supervised kernel matrix learning which adaptively propagates the interactive information into the whole image, while successfully keeping the original data coherence. Moreover, ACP Cut adopts seed propagation to achieve discriminative structure learning and reduce the computational complexity. Experimental results demonstrate that the ACP Cut extracts foreground objects successfully from the background and outperforms the state-of-the-art methods for interactive image segmentation in terms of both effectiveness and efficiency.

📚REFERENCE:
Meng Jian and Cheolkon Jung, Member, IEEE, “Interactive Image Segmentation Using Adaptive Constraint Propagation”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 25, NO. 3, MARCH 2016.

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