PROJECT TITLE :

Salient Region Detection via High-Dimensional Color Transform and Local Spatial Support

ABSTRACT:

In this paper, we tend to introduce a completely unique approach to automatically detect salient regions in an image. Our approach consists of worldwide and local options, which complement every different to compute a saliency map. The first key idea of our work is to create a saliency map of a picture by employing a linear combination of colors during a high-dimensional color area. This can be based mostly on an observation that salient regions often have distinctive colors compared with backgrounds in human perception, but, human perception is sophisticated and highly nonlinear. By mapping the low-dimensional red, inexperienced, and blue color to a feature vector in an exceedingly high-dimensional color space, we tend to show that we have a tendency to can composite an correct saliency map by finding the optimal linear combination of color coefficients in the high-dimensional color space. To additional improve the performance of our saliency estimation, our second key idea is to utilize relative location and color distinction between superpixels as features and to resolve the saliency estimation from a trimap via a learning-primarily based algorithm. The further local features and learning-primarily based algorithm complement the worldwide estimation from the high-dimensional color remodel-primarily based algorithm. The experimental results on three benchmark datasets show that our approach is effective compared with the previous state-of-the-art saliency estimation strategies.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : Residual Learning for Salient Object Detection ABSTRACT: Most recently developed salient object detection deep learning algorithms use multi-scale methodologies and fully convolutional neural networks to enhance
PROJECT TITLE : Reverse Attention-Based Residual Network for Salient Object Detection ABSTRACT: Recent advances in salient object detection have been made thanks to the rapid development of deep convolutional neural networks,
PROJECT TITLE : RGB-T Salient Object Detection via Fusing Multi-Level CNN Features ABSTRACT: Deep convolutional neural networks have lately made significant progress in the field of RGB-inducing salient object recognition (CNNs).
PROJECT TITLE : Focal Boundary Guided Salient Object Detection ABSTRACT: The use of deep convolutional networks has significantly improved the performance of salient object segmentation. However, these networks often yield blob-like
PROJECT TITLE : Salient Object Detection With Lossless Feature Reflection and Weighted Structural Loss ABSTRACT: As more and more real-world applications emerge, salient object identification, which tries to identify and find

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry