Color Segmentation Based on Human Perception Using Fuzzy Logic

Author(s):  
Tin Mar Kyi ◽  
Khin Chan Myae Zin
2017 ◽  
Vol 28 (2) ◽  
pp. 212-231 ◽  
Author(s):  
Bharat Singh Patel ◽  
Cherian Samuel ◽  
S.K. Sharma

Purpose The purpose of this paper is to report a case study carried out to assess the agility and identify obstacles to agility in a supply chain. A human perception-based framework is used for the calculation of agility. The case study was carried out in a North India-based manufacturing organization. Design/methodology/approach In this study, the concept of a multi-grade fuzzy logic approach is used. Using this concept, the overall agility index has been determined. The fuzzy logic approach has been used to overcome the disadvantages such as impreciseness and vagueness using a scoring method. Findings From the analysis, it is observed that the organization on which the study was performed is “very agile.” After evaluating the agility level, the fuzzy performance importance index is calculated, which helps to identify the barriers of agility in the supply chain. These barriers help decision makers to implement appropriate improvement measures for improving agility level. Overall, 11 barriers were identified in the study. Research limitations/implications Managers of the contemporary manufacturing organization have to measure the agility level of the organization and identify barriers to agility in order to survive in a competitive environment. The obstacles identified in this study are used to improve the performance of the organization. The enterprise should improve on the weak areas in order to achieve the highest agility level. Originality/value The agile supply chain (ASC) enablers proposed by previous researchers are not sufficient for the evaluation of agility of a supply chain. There are a few more ASC enablers such as customer satisfaction, flexibility and adaptability that also play a vital role in making a supply chain agile. Adding these three ASC enablers, a total of seven ASC enablers along with their attributes are being considered for the development of a conceptual model.


2013 ◽  
Author(s):  
Guoxin Zhao ◽  
Yunyi Li ◽  
Genshe Chen ◽  
Qinghao Meng ◽  
Wei Li

2019 ◽  
Vol 2019 (1) ◽  
pp. 369-374
Author(s):  
Gianluigi Ciocca ◽  
Paolo Napoletano ◽  
Raimondo Schettini ◽  
Isabella Gagliardi ◽  
Maria Teresa Artese

Color of food images play a key role in human perception of food quality and calories, as well as in food choice. In this paper we investigate the use of computational methods for color harmony analysis of food images. To this end we propose a computational pipeline that includes color segmentation, color palette extraction and color harmony prediction. Such a pipeline makes it possible to analyze the emotions elicited by pairs and multiple combinations of food dishes.


AMBIO ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 467-478 ◽  
Author(s):  
Dulce M. Ruíz-López ◽  
Alberto E. Aragón-Noriega ◽  
Antonio Luna-Gonzalez ◽  
Hector A. Gonzalez-Ocampo

2016 ◽  
Vol 52 (7) ◽  
pp. 1474-1477 ◽  
Author(s):  
Pier Luigi Gentili ◽  
Amanda L. Rightler ◽  
B. Mark Heron ◽  
Christopher D. Gabbutt

Biologically inspired fuzzy logic systems allow us to detect and discern UV frequencies.


Author(s):  
Hangyao Wu ◽  
Zeshui XU

During the last decades, the art and science of fuzzy logic have witnessed significant developments and have found applications in many active areas, such as pattern recognition, classification, control systems, etc. A lot of research has demonstrated the ability of fuzzy logic in dealing with vague and uncertain linguistic information. For the purpose of representing human perception, fuzzy logic has been employed as an effective tool in intelligent decision making. Due to the emergence of various studies on fuzzy logic-based decision-making methods, it is necessary to make a comprehensive overview of published papers in this field and their applications. This paper covers a wide range of both theoretical and practical applications of fuzzy logic in decision making. It has been grouped into five parts: to explain the role of fuzzy logic in decision making, we first present some basic ideas underlying different types of fuzzy logic and the structure of the fuzzy logic system. Then, we make a review of evaluation methods, prediction methods, decision support algorithms, group decision-making methods based on fuzzy logic. Applications of these methods are further reviewed. Finally, some challenges and future trends are given from different perspectives. This paper illustrates that the combination of fuzzy logic and decision making method has an extensive research prospect. It can help researchers to identify the frontiers of fuzzy logic in the field of decision making.


2015 ◽  
Vol 20 (6) ◽  
pp. 3276-3284 ◽  
Author(s):  
Houshyar Asadi ◽  
Shady Mohamed ◽  
Saeid Nahavandi

2017 ◽  
Vol 131 (1) ◽  
pp. 19-29 ◽  
Author(s):  
Marianne T. E. Heberlein ◽  
Dennis C. Turner ◽  
Marta B. Manser

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