Color image segmentation considering of human sensitivity for color pattern variations

نویسندگان

  • Kuk-Jin Yoon
  • In-So Kweon
چکیده

Color image segmentation plays an important role in the computer vision and image processing area. In this paper, we propose a novel color image segmentation algorithm in consideration of human visual sensitivity for color pattern variations by generalizing K-means clustering. Human visual system has different color perception sensitivity according to the spatial color pattern variation. To reflect this effect, we define the CCM (Color Complexity Measure) by calculating the absolute deviation with Gaussian weighting within the local mask and assign weight value to each color vector using the CCM values. Weighted color vectors are used in K-Means algorithm and the shape and the center position of each cluster is formed according to the color distribution in the image. We adaptively determine optimal K value, which is the number of cluster, by using the statistics of the color complexity measure that implies the complexity of the color image. The experimental results show that proposed algorithm segments the color image preserving significant features while removing unimportant details.

برای دانلود 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

Performance Analysis of Segmentation of Hyperspectral Images Based on Color Image Segmentation

Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without tex...

متن کامل

Robust Potato Color Image Segmentation using Adaptive Fuzzy Inference System

Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...

متن کامل

Modified CLPSO-based fuzzy classification System: Color Image Segmentation

Fuzzy segmentation is an effective way of segmenting out objects in images containing both random noise and varying illumination. In this paper, a modified method based on the Comprehensive Learning Particle Swarm Optimization (CLPSO) is proposed for pixel classification in HSI color space by selecting a fuzzy classification system with minimum number of fuzzy rules and minimum number of incorr...

متن کامل

Color Reduction in Hand-drawn Persian Carpet Cartoons before Discretization using image segmentation and finding edgy regions

In this paper, we present a method for color reduction of Persian carpet cartoons that increases both speed and accuracy of editing. Carpet cartoons are in two categories: machine-printed and hand-drawn. Hand-drawn cartoons are divided into two groups: before and after discretization. The purpose of this study is color reduction of hand-drawn cartoons before discretization. The proposed algorit...

متن کامل

Adaptive Region Merging Approach for Morphological Color Image Segmentation

This study we focus on the morphological-based image segmentation problem, based on the watershed pre-segmentation with color-alone feature. Based on the color mathematical morphology (MM) method, the similarity measure of merging process between neighboring pixels and regions can be performed as a ranking problem. To avoid the creation of a false color and false segmentation, a hybrid-ordering...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002