• Title/Summary/Keyword: aggregate segmentation

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Segmentation of Natural Fine Aggregates in Micro-CT Microstructures of Recycled Aggregates Using Unet-VGG16 (Unet-VGG16 모델을 활용한 순환골재 마이크로-CT 미세구조의 천연골재 분할)

  • Sung-Wook Hong;Deokgi Mun;Se-Yun Kim;Tong-Seok Han
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.37 no.2
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    • pp.143-149
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    • 2024
  • Segmentation of material phases through image analysis is essential for analyzing the microstructure of materials. Micro-CT images exhibit variations in grayscale values depending on the phases constituting the material. Phase segmentation is generally achieved by comparing the grayscale values in the images. In the case of waste concrete used as a recycled aggregate, it is challenging to distinguish between hydrated cement paste and natural aggregates, as these components exhibit similar grayscale values in micro-CT images. In this study, we propose a method for automatically separating the aggregates in concrete, in micro-CT images. Utilizing the Unet-VGG16 deep-learning network, we introduce a technique for segmenting the 2D aggregate images and stacking them to obtain 3D aggregate images. Image filtering is employed to separate aggregate particles from the selected 3D aggregate images. The performance of aggregate segmentation is validated through accuracy, precision, recall, and F1-score assessments.

Adaptive Multi-class Segmentation Model of Aggregate Image Based on Improved Sparrow Search Algorithm

  • Mengfei Wang;Weixing Wang;Sheng Feng;Limin Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.2
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    • pp.391-411
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    • 2023
  • Aggregates play the skeleton and supporting role in the construction field, high-precision measurement and high-efficiency analysis of aggregates are frequently employed to evaluate the project quality. Aiming at the unbalanced operation time and segmentation accuracy for multi-class segmentation algorithms of aggregate images, a Chaotic Sparrow Search Algorithm (CSSA) is put forward to optimize it. In this algorithm, the chaotic map is combined with the sinusoidal dynamic weight and the elite mutation strategies; and it is firstly proposed to promote the SSA's optimization accuracy and stability without reducing the SSA's speed. The CSSA is utilized to optimize the popular multi-class segmentation algorithm-Multiple Entropy Thresholding (MET). By taking three METs as objective functions, i.e., Kapur Entropy, Minimum-cross Entropy and Renyi Entropy, the CSSA is implemented to quickly and automatically calculate the extreme value of the function and get the corresponding correct thresholds. The image adaptive multi-class segmentation model is called CSSA-MET. In order to comprehensively evaluate it, a new parameter I based on the segmentation accuracy and processing speed is constructed. The results reveal that the CSSA outperforms the other seven methods of optimization performance, as well as the quality evaluation of aggregate images segmented by the CSSA-MET, and the speed and accuracy are balanced. In particular, the highest I value can be obtained when the CSSA is applied to optimize the Renyi Entropy, which indicates that this combination is more suitable for segmenting the aggregate images.

Examination of Aggregate Quality Using Image Processing Based on Deep-Learning (딥러닝 기반 영상처리를 이용한 골재 품질 검사)

  • Kim, Seong Kyu;Choi, Woo Bin;Lee, Jong Se;Lee, Won Gok;Choi, Gun Oh;Bae, You Suk
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.6
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    • pp.255-266
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    • 2022
  • The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.

Development of Aggregate Recognition Algorithm for Analysis of Aggregate Size and Distribution Attributes (골재 크기와 분포 특성을 분석하기 위한 골재 인식 알고리즘 개발)

  • Seo, Myoung Kook;Lee, Ho Yeon
    • Journal of Drive and Control
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    • v.19 no.3
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    • pp.16-22
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    • 2022
  • Crushers are equipment that crush natural stones, to produce aggregates used at construction sites. As the crusher proceeds, the inner liner becomes worn, causing the size of the aggregate produced to gradually increase. The vision sensor-based aggregate analysis system analyzes the size and distribution of aggregates in production, in real time through image analysis. This study developed an algorithm that can segmentate aggregates in images in real time. using image preprocessing technology combining various filters and morphology techniques, and aggregate region characteristics such as convex hull and concave hull. We applied the developed algorithm to fine aggregate, intermediate aggregate, and thick aggregate images to verify their performance.

A methodology for spatial distribution of grain and voids in self compacting concrete using digital image processing methods

  • Onal, Okan;Ozden, Gurkan;Felekoglu, Burak
    • Computers and Concrete
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    • v.5 no.1
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    • pp.61-74
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    • 2008
  • Digital image processing algorithms for the analysis and characterization of grains and voids in cemented materials were developed using toolbox functions of a mathematical software package. Utilization of grayscale, color and watershed segmentation algorithms and their performances were demonstrated on artificially prepared self-compacting concrete (SCC) samples. It has been found that color segmentation was more advantageous over the gray scale segmentation for the detection of voids whereas the latter method provided satisfying results for the aggregate grains due to the sharp contrast between their colors and the cohesive matrix. The watershed segmentation method, on the other hand, appeared to be very efficient while separating touching objects in digital images.

Morphological Operations to Segment a Tumor from a Magnetic Resonance Image

  • Thapaliya, Kiran;Kwon, Goo-Rak
    • Journal of information and communication convergence engineering
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    • v.12 no.1
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    • pp.60-65
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    • 2014
  • This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. After the enhancement process, the thresholding value is calculated using the mean and the standard deviation of the image. This thresholding value is used to binarize the image followed by the morphological operations. Moreover, the combination of these morphological operations allows to compute the local thresholding image supported by a flood-fill algorithm and a pixel replacement process to extract the tumor from the brain. Thus, this framework provides a new source of evidence in the field of segmentation that the specialist can aggregate with the segmentation results in order to soften his/her own decision.

Bird's Eye View Semantic Segmentation based on Improved Transformer for Automatic Annotation

  • Tianjiao Liang;Weiguo Pan;Hong Bao;Xinyue Fan;Han Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.8
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    • pp.1996-2015
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    • 2023
  • High-definition (HD) maps can provide precise road information that enables an autonomous driving system to effectively navigate a vehicle. Recent research has focused on leveraging semantic segmentation to achieve automatic annotation of HD maps. However, the existing methods suffer from low recognition accuracy in automatic driving scenarios, leading to inefficient annotation processes. In this paper, we propose a novel semantic segmentation method for automatic HD map annotation. Our approach introduces a new encoder, known as the convolutional transformer hybrid encoder, to enhance the model's feature extraction capabilities. Additionally, we propose a multi-level fusion module that enables the model to aggregate different levels of detail and semantic information. Furthermore, we present a novel decoupled boundary joint decoder to improve the model's ability to handle the boundary between categories. To evaluate our method, we conducted experiments using the Bird's Eye View point cloud images dataset and Cityscapes dataset. Comparative analysis against stateof-the-art methods demonstrates that our model achieves the highest performance. Specifically, our model achieves an mIoU of 56.26%, surpassing the results of SegFormer with an mIoU of 1.47%. This innovative promises to significantly enhance the efficiency of HD map automatic annotation.

Modeling the Price-Reduction Effect in Mobile Telecommunications Traffic

  • Cha Kyoung Cheon;Jun Duk Bin;Wilson Amy R.
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.10a
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    • pp.289-303
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    • 2004
  • As needs for telecommunications services diversify, an increasingly wide range of telecommunications services is becoming available in the market. Any subscriber can find a service to satisfy his/her telecommunication requirements and competition between providers to retain heavy users is increasing. Service price reductions are one retention strategy, although price reductions for one service can affect the individual-level usage for other services. Price reductions can also be imposed on a service provider by regulation. For these reasons, understanding how price reductions affect service usage is of growing importance to the telecommunications industry for purposes of pricing and tariff development. In this paper, we develop an individual-level usage model for telecommunications services and analyze the effects on usage of a price reduction. We apply the model to age-stratified aggregate traffic data for a Korean mobile telecommunication service provider. Finally, we develop a model to support a market segmentation and price reduction strategy.

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A Study on the Consumer's Service Quality Perception Based on the Types of Life-style (소비자의 라이프스타일에 따른 서비스품질 지각 차이에 관한 연구)

  • Park, Yoon-Seo;Lee, Seung-In;Choi, In
    • Journal of Global Scholars of Marketing Science
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    • v.19 no.2
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    • pp.53-67
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    • 2009
  • For the last decades, service quality has been studied as one of the most important tools for a service company to compete with the other companies. Based on these past researches, it has been agreed that the service quality is a basic and powerful tool to create the competitive advantage. Due to similar reason, many service marketing practitioners have been also focused on the service quality to retain the existing consumers and collect the new consumers. However, service quality is subjectively perceived by individual consumers. Consumer evaluation of service quality can be different from each other. Especially consumers with one life-style may evaluate the service quality differently from the consumers with the other life-styles. Therefore we need to know whether there are differences in service quality perception on the categories of life-style. Life-style refers to a distinctive mode of living in its aggregate and broadest sense. It embodies the patterns that were developed and emerged from the dynamics of living in a society. Since the concept of life-style and its relationship to marketing was introduced in 1963 by William Lazer, methods of measuring the life-style and their application have been developed. Life-style has been usually used to segment the marketplace because it offers marketers a unique and important view of the market. When Life-style is combined with clustering methods, life-style segmentation can generate identifiable whole persons rather than isolated fragment. Life-style segmentation begins with people instead of products and classifies them into different life-style types, each characterized by a unique style of living based on a wide range of activities, interests, and opinions(Plummer, 1974). In this study we applies the life-style segmentation based on the AIO(Activities, Interests, and Opinions) to the consumers of the large discount stores. In Korea, the large discount store market has entered into maturity stage so that the market differentiation strategy is becoming a more critical issue to the marketing practitioners. One of the most important tools to differentiate from the competitors in large discount store market is continuously to provide service of better quality than competitors. This study tries to find answers about the following questions: 1) How can we categorize the consumer life-styles in the large discount store? 2) What are the characteristics of the categorized groups? 3) Are there any differences in service quality perception among the consumers with different life-styles 4) Are there any differences in consumer behavior among them in the large discount store? For the purpose, we collected survey data from consumers and analyzed the data with the SPSS package where we had $X^2$-test, factor analysis, ANOVA, MANOVA, and cluster analysis. The survey was made during one month in the April of 2008. Among the collected 306 copies of questionnaires, 281 copies were chosen as the effective samples for empirical analysis except 25 copies with wrong responses. To identify the life-style patterns, we used the measures employed by Kim and Kwon(1999), where 44 items on a seven-point scale were used to measure factors of the life-style patterns. The Principal Component Method was used for factor extraction, and the VARIMAX orthogonal factor rotation was employed. The 7 items showing low factor loading were eliminated. The results of the factor analysis suggested that nine factors of the life-style patterns were identified as follows: 1) the equality-of-sexes and pursuit-of-independence tendency 2) self-management tendency 3) sociable tendency 4) self-display tendency 5) degree of a dilettante life 6) pursuit-of-information tendency 7) bargain hunter tendency 8) TV preference tendency 9) pursuit-of-leisure tendency. Next, after the K-means cluster analysis was performed with nine factors of the life-style patterns, the life-styles of the respondents were classified into four groups which are named as the 'progressive practicality-oriented group', 'positive success-oriented group', 'sociable ostentation-oriented group', 'stable conservation-oriented group'. The analysis results for usage behavior between the market segments showed statistically significant differences in the frequency of usage, duration time in the store, consumer satisfaction, and loyalty. Also, we tried to investigate whether the large discount store consumers differently perceive the quality of service based upon the types of life-style. To measure the service quality of large discount store, we adapted several measurement models measuring the service quality such as SERVPERF, BCP, R-SERVPERF, R-BCP. MANOVA and One-Way ANOVA were performed to confirm the difference in service quality perception based on the market segments. The results have also shown significant differences between life-style types in service quality perception. These findings show that the large discount store marketers should consider consumer life-style as one of the most important market segments for marketing and understand the difference in service quality perception between life-style types. Our findings give important implications to marketers of large discount stores as well as life-style researchers. First, this study showed there were significant differences in consumer's service quality perception and usage behavior between the types of life-style. It provides evidence that the life-style approach can be a important basis in segmenting the large discount store market and will make consumers perceive the service quality high. Second, most previous researches on service quality have been in aggregate level. However, our results imply that the future research on service quality have to focus on segment level.

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Mechanical Properties Evaluation of 3D Printing Recycled Concrete utilizing Wasted Shell Aggregate (패각 잔골재를 활용한 3D 프린팅 자원순환 콘크리트의 역학적 성능 평가)

  • Jeewoo Suh;Ju-Hyeon Park;Tong-Seok Han
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.37 no.1
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    • pp.33-40
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    • 2024
  • The volume of shells, a prominent form of marine waste, is steadily increasing each year. However, a significant portion of these shells is either discarded or left near coastlines, posing environmental and social concerns. Utilizing shells as a substitute for traditional aggregates presents a potential solution, especially considering the diminishing availability of natural aggregates. This approach could effectively reduce transportation logistics costs, thereby promoting resource recycling. In this study, we explore the feasibility of employing wasted shell aggregates in 3D concrete printing technology for marine structures. Despite the advantages, it is observed that 3D printing concrete with wasted shells as aggregates results in lower strength compared to ordinary concrete, attributed to pores at the interface of shells and cement paste. Microstructure characterization becomes essential for evaluating mechanical properties. We conduct an analysis of the mechanical properties and microstructure of 3D printing concrete specimens incorporating wasted shells. Additionally, a mix design is proposed, taking into account flowability, extrudability, and buildability. To assess mechanical properties, compression and bonding strength specimens are fabricated using a 3D printer, and subsequent strength tests are conducted. Microstructure characteristics are analyzed through scanning electron microscope tests, providing high-resolution images. A histogram-based segmentation method is applied to segment pores, and porosity is compared based on the type of wasted shell. Pore characteristics are quantified using a probability function, establishing a correlation between the mechanical properties and microstructure characteristics of the specimens according to the type of wasted shell.