554 research outputs found
Texture Image Segmentation using Morphology in Wavelet Transforms
One of the essential and crucial steps for image understanding, interpretation, analysis and recognition is the image segmentation. This paper advocates a new segme- ntation scheme using morphology on wavelet decomposed images. The present paper provides a good segmentation on natural images and textures by dividing an image into non overlapping regions, which are homogenous in terms of certain features such as texture, spatial coordinates etc. using simple morphological operations. Morphological enhancement technique based on Top Hat transforms enhances the local contrast in this paper. The morphological treatment and followed by Otsu2019;s threshold overcomes the problem of noise and thin gaps, and also smooth the final regions. The experimental results on four different databases demonstrate the success of the proposed method, compared to many other methods
Redundancy Allocation of Partitioned Linear Block Codes
Most memories suffer from both permanent defects and intermittent random
errors. The partitioned linear block codes (PLBC) were proposed by Heegard to
efficiently mask stuck-at defects and correct random errors. The PLBC have two
separate redundancy parts for defects and random errors. In this paper, we
investigate the allocation of redundancy between these two parts. The optimal
redundancy allocation will be investigated using simulations and the simulation
results show that the PLBC can significantly reduce the probability of decoding
failure in memory with defects. In addition, we will derive the upper bound on
the probability of decoding failure of PLBC and estimate the optimal redundancy
allocation using this upper bound. The estimated redundancy allocation matches
the optimal redundancy allocation well.Comment: 5 pages, 2 figures, to appear in IEEE International Symposium on
Information Theory (ISIT), Jul. 201
Image Retrieval based on Macro Regions
Various image retrieval methods are derived using local features, and among them the local binary pattern (LBP) approach is very famous. The basic disadvantage of these methods is they completely fail in representing features derived from large or macro structures or regions, which are very much essential to represent natural images. To address this multi block LBP are proposed in the literature. The other disadvantage of LBP and LTP based methods are they derive a coded image which ranges 0 to 255 and 0 to 3561 respectively. If one wants to integrate the structural texture features by deriving grey level co-occurrence matrix (GLCM), then GLCM ranges from 256 x 256 and 3562 x 3562 in case of LBP and LTP respectively. The present paper proposes a new scheme called multi region quantized LBP (MR-QLBP) to overcome the above disadvantages by quantizing the LBP codes on a multi-region, thus to derive more precisely and comprehensively the texture features to provide a better retrieval rate. The proposed method is experimented on Corel database and the experimental results indicate the efficiency of the proposed method over the other methods
A Heuristic Based Multi-Objective Approach for Network Reconfiguration of Distribution Systems
This paper presents an algorithm for network reconfiguration based on the heuristic rules and fuzzy multi-objective approach with an improved Fast Decoupled load flow algorithm. Multiple objectives are considered to minimize the real power loss, deviation in bus voltages, branch current violation and for load balancing among feeders, while subjected to a radial network structure in which all loads kept energized. These four objectives are modeled with fuzzy sets to evaluate their imprecise nature. Heuristic rules are also incorporated in the algorithm for drastically minimizing the number of tie-switch operations. An improved Fast Decoupled load flow algorithm with Single Matrix Model (FDC-SMM) has been proposed for distribution networks. The proposed algorithm is very effective in dealing with reconfiguration problems of single and multi-feeder networks Keywords: Multi-objective approach, Reconfiguration, Fuzzy set theory, Fast decoupled load flo
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