Yukari Hagihara

2-D direction histogram based entropic thresholding

Abstract Local image features are effective descriptors for image analysis and are also important cues for image segmentation. In this paper, we propose a novel entropic thresholding approach. This approach incorporates local features into a conventional entropic method to implement the thresholding. The local features are obtained from an orientation histogram to describe the edge property of the local neighborhood. To verify the performance of our method, thresholding was carried out on different types of images and compared with some well-known entropic approaches. Experimental results show that using the local edge property can give a better thresholding result.

Automatic Image Enhancement by Artificial Bee Colony Algorithm

With regard to the improvement of image quality, image enhancement is an important process to assist human with better perception. This paper presents an automatic image enhancement method based on Artificial Bee Colony (ABC) algorithm. In this method, ABC algorithm is applied to find the optimum parameters of a transformation function, which is used in the enhancement by utilizing the local and global information of the image. In order to solve the optimization problem by ABC algorithm, an objective criterion in terms of the entropy and edge information is introduced to measure the image quality to make the enhancement as an automatic process. Several images are utilized in experiments to make a comparison with other enhancement methods, which are genetic algorithm-based and particle swarm optimization algorithm-based image enhancement methods.

HACC: Heterogeneous-aware cooperative clustering hierarchy for wireless sensor networks

In this paper we present a low complexity cooperative diversity clustering protocol for heterogeneous wireless sensor networks. Here we analyze the impact of heterogeneity of nodes in terms of their energy in wireless sensor networks that are clustered in a co-operative fashion to prolong the effective network lifetime. In contrast to these approaches, we propose HACC, a heterogeneous-aware cooperative clustered scheme for wireless sensor networks based on weighted election probabilities of each node to become a cluster head according to its residual energy. We then propose a simple modification in the clustering algorithm to exploit virtual MIMO based cooperative transmission. In place of selecting a single cluster head at network layer, we proposed multiple cluster heads in each cluster to obtain a full diversity gain over long distance communication without sacrificing transmission data rate, and established virtual MIMO based cooperative transmission. We treated the cooperative cluster head selection method as a Facility Location Problem (FLP) to gain better energy utilization. Finally, the simulation results demonstrate that our cooperative clustering approach is more effective in prolonging the time interval before the death of the first node (we refer to as stability period) compared to the one obtained using current clustering protocols, and observe that this proposal can achieve higher order diversity gain with improved spectral efficiency when the distance to Base Station is over a given threshold.

Development of Electric Rust Preventive Machining Method -Water Using for Machining: Improvement of Water Recycle System-

Currently, the machining fluid includes several chemicals such as cutting oil and grinding oil is used for the machining. However, such the machining fluid that is caused enormous disposal cost and environmental load, should reduce using. Therefore, in this investigation, electric rust preventive machining method which uses only water for machining fluid is developed. Because using only water without extreme pressure agents, oil and so on, this method decreases disposal of waste machining fluid. In this paper, the system to remove impurities from a used machining fluid, and to reuse machining fluid is designed. To reproduce water efficiently, the order of arranging the filter is changed. In consequence, it has been efficient when the filtration filter is set up first, and the activated carbon filter is set up in the second. In addition, the reproduction of the water when the supply pressure is 0.75 MPa is verified by using this system. As a result, the water which passed a water recycle system, the impurities such as iron, conductivity, turbidity, colour decreased, and purification of the water is possible for this system. And, 5.2 L/min refined water recycle is achieved.

A New Two-Dimensional Direction Histogram Based Entropic Thresholding

Since the entropic concept was introduced in image segmentation by Pun, many entropic methods have been developed in rapid succession. Consequently, the entropic approach has become a major category of segmentation. Abutaleb et al. firstly introduced the two-dimensional entropies, taking the spatial correlation into account. However, their method takes up too much computational time to give better results. In this paper, a new entropic thresholding method is proposed based on the two-dimensional Shannon entropies by using the orientation histogram. Utilizing several images, the new method is compared with Abutalebs method and the two-dimensional entropic thresholding method proposed by Xiao et al. The experimental results demonstrate the effectiveness of the proposed method in aspects of two-dimensional entropic thresholding.