Image Segmentation for Uneven Lighting Images using Adaptive Thresholding and Dynamic Window based on Incremental Window Growing Approach

Saini, Rashmi; Dutta, Maitreyee
October 2012
International Journal of Computer Applications;10/15/2012, Vol. 56, p31
Academic Journal
This paper proposes a novel method to address the problem of segmentation, for uneven lighting images. Though there are many segmentation methods, but most of them are based on either the fixed window method or window merging technique. Limitation of such methods is that, initial size of window is selected manually and segmentation accuracy greatly depends upon the proper choice of initial window size. In the proposed work, problem of uneven illumination condition has been addressed using dynamic window growing approach. The proposed algorithm is based on an incremental window growing approach using entropy based selection criteria. The window thus fixed by the selection criteria are considered as sub-images and each sub-images has been segmented by using minimum standard deviation difference based thresholding to improve the segmentation result. The result of the experiments show that the proposed method can deal with higher number of segmentation problem and improve the overall performance for uneven lighting image segmentation.


Related Articles

  • Efficient Character Segmentation using Adaptive Binarization and Connected Components Analysis in Ubiquitous Computing Environments. Jongho Kim; YongYun Cho // International Journal of Multimedia & Ubiquitous Engineering;Mar2013, Vol. 8 Issue 2, p89 

    In ubiquitous computing environments, many applications are devised to provide autonomous services. To make services autonomous, each service has to inevitably recognize the deployed devices or objects in ubiquitous computing environments. In order to provide an autonomous service based on...

  • An Adaptative Multi-Agent System Approach for Image Segmentation. Mohammed, Redjimi; Said, Amri // International Journal of Computer Applications;8/1/2012, Vol. 51, p21 

    This article presents a multi-agent approach for the segmentation of images. A multi-agent system (MAS) is a distributed system consisting of a set of agents that interact with themselves in an environment they are able to perceive and on which they can act. The proposed solution consists in...

  • An Adpative Thresholding Segmentation Algorithm based on Spatial Distances. Xijuan Guo; Jiao Zheng; Zheng Chang // Journal of Convergence Information Technology;Mar2013, Vol. 8 Issue 5, p1026 

    Most thresholding segmentation algorithms for grayscale image processing only take the gray-scale property into consideration without investigating the spatial relationship of the pixels. As a result, segmentation results are discontinuous and inaccurate. Moreover, recent work mainly focus on...

  • An Adaptive Spectral Clustering Algorithm for Image Clustering and Segmentation. Gu Ruijun; Chen Shenglei; Wang Jiacai // Information Technology Journal;2013, Vol. 12 Issue 22, p6763 

    Based on clustering consistency, the proposed method first emphasizes the flexibility of the local scale, which means each sample has a corresponding scale parameter. Further more, it overcomes the limitations of traditional methods in all samples with the same global scale parameter. Secondly,...

  • APTIVE IMAGE SEGMENTATION BASED ON SALIENCY DETECTION. Shui Linlin // International Journal on Smart Sensing & Intelligent Systems;Mar2015, Vol. 8 Issue 1, p408 

    in this article, we propose an adaptive image segmentation method based on saliency. First of all, we obtain the saliency map of an image via four bottom-layer feature tunnels, i.e. color, intensity, direction and energy. The energy tunnel helps to describe the outline of objects better in the...

  • Brain MR Image Segmentation Based on an Adaptive Combination of Global and Local Fuzzy Energy. Wenchao Cui; Yi Wang; Tao Lei; Yangyu Fan; Yan Feng // Mathematical Problems in Engineering;2013, p1 

    This paper presents a novel fuzzy algorithm for segmentation of brain MR images and simultaneous estimation of intensity inhomogeneity. The proposed algorithm defines an objective function including a local fuzzy energy and a global fuzzy energy. Based on the assumption that the local image...

  • Semi-automatic segmentation of myocardium at risk in T2-weighted cardiovascular magnetic resonance.  // Journal of Cardiovascular Magnetic Resonance (BioMed Central);2012, Vol. 14 Issue 1, p10 

    The article presents a study developing an automatic segmentation algorithm for quantification of myocardium at risk (MaR) in T2-weighted cardiovascular magnetic resonance (CMR), a priori knowledge on the appearance of MaR and cardiac anatomy. As mentioned, proposed algorithm was found to be a...

  • Sonar Image Segmentation Based on an Improved Selection of Initial Contour of Active Contour Model. Wu Junpeng; Guo Haitao // Applied Mechanics & Materials;2014, Vol. 709, p447 

    The correct sonar image segmentation is an important foundation for underwater target recognition. Because the contour convergence of the active contour model depends on the selection of initial position, the active contour model is applied in sonar image segmentation. This paper proposed a...

  • Environmentally Adaptive Segmentation Algorithm for Outdoor Crops Using Gaussian Mixture Model. Zhenghong Yu; Hongmei Wang // Advanced Materials Research;2014, Vol. 1049-1050, p1747 

    Crop segmentation from outdoor images is still an open problem. In this paper, we proposed a novel crop segmentation method using Gaussian Mixture Model (GMM), which is robust and not sensitive to the challenging outdoor light conditions and complex environmental elements. The method mainly...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics