Image segmentation based on the hybrid total variation model and the K-means clustering strategy

Image segmentation based on the hybrid total variation model and the K-means clustering strategy

Abstract The performance of image segmentation highly relies on the original inputting image. When the image is contaminated by some noises or blurs, we can not obtain the efficient segmentation result by using direct segmentation methods. In order to efficiently segment the contaminated image, this paper proposes a two step method based on the hybrid total variation model with a box constraint...

Image Restoration Based on the Hybrid Total-Variation-Type Model

and Applied Analysis 3 function. Since the edge detector function g : g u0 : 1/ 1 |∇ u0 ∗Gσ x | with Gσ x 1/2πσ2 exp − x2/2σ2 can depict the information of edges, we can employ it as a balance function; that is, we can apply the following model: min u β 2 ‖u − u0‖L2 ∣ ∣1 − gu∣∣BV ∣ ∣gu ∣ ∣ BV 2 1.7 to restore the noisy image 16 . Obviously, | 1 − g u|BV tends to be predominant where edges most ...

K - Means Clustering for Automatic Image Segmentation

Comparing Model-based Versus K-means Clustering for the Planar Shapes

‎In some fields‎, ‎there is an interest in distinguishing different geometrical objects from each other‎. ‎A field of research that studies the objects from a statistical point of view‎, ‎provided they are‎ ‎invariant under translation‎, ‎rotation and scaling effects‎, ‎is known as the statistical shape analysis‎. ‎Having some objects that are registered using key points on the outline...

Persistent K-Means: Stable Data Clustering Algorithm Based on K-Means Algorithm

Identifying clusters or clustering is an important aspect of data analysis. It is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. It is a main task of exploratory data mining, and a common technique for statistical data analysis This paper proposed an improved version of K-Means algorithm, namely Persistent K...