Image Transformation using Modified K- means clustering algorithm for Parallel saliency map

نویسنده

  • Aman Sharma
چکیده

Abstract— to design an image transformation system is Depending on the transform chosen, the input and output images may appear entirely different and have different interpretations. Image Transformation with the help of certain module like input image, image cluster index, object in cluster and color index transformation of image. K-means clustering algorithm is used to cluster the image for better segmentation. In the proposed method parallel saliency algorithm with K-means clustering is used to avoid local minima and to find the saliency map. The region behind that of using parallel saliency algorithm is proved to be more than exiting saliency algorithm. Keywordparallel saliency algorithm, Image Transformation, saliency map, Kmeans clustering algorithm, morphology.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

High Performance Implementation of Fuzzy C-Means and Watershed Algorithms for MRI Segmentation

Image segmentation is one of the most common steps in digital image processing. The area many image segmentation algorithms (e.g., thresholding, edge detection, and region growing) employed for classifying a digital image into different segments. In this connection, finding a suitable algorithm for medical image segmentation is a challenging task due to mainly the noise, low contrast, and steep...

متن کامل

High Performance Implementation of Fuzzy C-Means and Watershed Algorithms for MRI Segmentation

Image segmentation is one of the most common steps in digital image processing. The area many image segmentation algorithms (e.g., thresholding, edge detection, and region growing) employed for classifying a digital image into different segments. In this connection, finding a suitable algorithm for medical image segmentation is a challenging task due to mainly the noise, low contrast, and steep...

متن کامل

A Hybrid Data Clustering Algorithm Using Modified Krill Herd Algorithm and K-MEANS

Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...

متن کامل

A Survey Paper on an Efficient Salient Feature Extraction by Using Saliency Map Detection with Modified K-Means Clustering Technique

Human eye is perceptually more sensitive to certain colors and intensities and objects with such features are considered more salient. Detection of Salient image regions is useful in applications such as object based image retrieval, adaptive content delivery, adaptive region-of interest based image compression, and smart image resizing .This problem can be handled by mapping the pixels into va...

متن کامل

An Efficient Salient Feature Extraction by Using Saliency Map Detection with Modified K-Means Clustering Technique

Human eye is perceptually more sensitive to certain colors and intensities and objects with such features are considered more salient. Detection of Salient image regions is useful in applications such as object based image retrieval, adaptive content delivery, adaptive region-of interest based image compression, and smart image resizing .This problem can be handled by mapping the pixels into va...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013