本文關(guān)鍵詞：基于灰色系統(tǒng)理論的顯微纖維邊緣檢測系統(tǒng)研制　出處：《東華大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 纖維 邊緣檢測 灰色系統(tǒng)理論 灰色預(yù)測模型

【摘要】：伴隨經(jīng)濟(jì)技術(shù)的飛躍,纖維在社會各領(lǐng)域作用凸顯。纖維的成分及質(zhì)量決定了其性能和價格,而檢測出的纖維邊緣的連續(xù)性與完整性又對纖維特征提取、目標(biāo)分離、模式識別及計算混紡比的準(zhǔn)確度影響很大。故纖維圖像的邊緣檢測是纖維自動識別體系中的關(guān)鍵一環(huán)。然而纖維在包埋、切片以及采樣過程中受到不均勻光照、聚焦、噪聲等方面的干擾,無法避免的出現(xiàn)顯微纖維圖像質(zhì)量差、背景區(qū)域與目標(biāo)纖維區(qū)分不明顯、輪廓不完整或者粘連等現(xiàn)象。而且傳統(tǒng)邊緣檢測算法獲取顯微纖維邊緣出現(xiàn)虛假、不連續(xù)邊緣和不能有效提取粘連纖維邊緣的問題。此外,出入境檢驗(yàn)檢疫局作為我國進(jìn)出口檢驗(yàn)驗(yàn)定的重要機(jī)關(guān),一直存在纖維成分檢測的相關(guān)問題,即雖耗費(fèi)一定的人力物力,但卻無法實(shí)現(xiàn)相對準(zhǔn)確的檢測及鑒證。故研究基于計算機(jī)數(shù)字圖像處理技術(shù),結(jié)合科學(xué)的灰色系統(tǒng)理論開展顯微纖維邊緣檢測是一項(xiàng)十分有意義的課題。本課題來源于國家自然科學(xué)基金面目項(xiàng)目《基于約束條件的非負(fù)矩陣分解算法及其在纖維自動識別中的應(yīng)用研究》(61472075)。作為在紡織、纖維和面料等學(xué)科上在國內(nèi)乃至世界上有極高學(xué)術(shù)地位的特色鮮明的高校,我校在棉麻以及化學(xué)纖維混紡領(lǐng)域研究成果積累頗豐。本文將探究初涉圖像邊緣檢測領(lǐng)域的灰色系統(tǒng)理論與現(xiàn)行的數(shù)字圖像處理技術(shù)相結(jié)合,把提取出連續(xù)、完整和準(zhǔn)確的顯微纖維邊緣作為研究的核心。本文綜合運(yùn)用灰色系統(tǒng)理論、NIBLACK算法和孔洞填充算法,提出了一套基于灰色系統(tǒng)理論的顯微纖維邊緣檢測技術(shù)路線,研制了顯微纖維邊緣自動檢測平臺系統(tǒng)。以顯微纖維圖像中各像素點(diǎn)為研究對象,基于灰色系統(tǒng)理論的邊緣檢測方案通過把GM(1,1)模型與NIBLACK算法相結(jié)合取得顯微纖維的強(qiáng)弱邊緣信息并實(shí)現(xiàn)有效的強(qiáng)弱邊緣連接再運(yùn)用孔洞填充算法來處理虛假邊緣以提取出完整的邊緣信息。針對基于灰色系統(tǒng)理論的顯微纖維邊緣檢測系統(tǒng)設(shè)計,從算法原理入手,充分利用灰色系統(tǒng)理論在我國學(xué)術(shù)研究體系中的強(qiáng)勢地位和先進(jìn)水平,發(fā)揮了灰色系統(tǒng)理論的“少數(shù)據(jù)貧信息”的建模特點(diǎn),展示了設(shè)計結(jié)果。實(shí)驗(yàn)結(jié)果表明,該算法能夠提取出精確連續(xù)完整的顯微纖維邊緣。
[Abstract]:With the leap of economy and technology, fiber plays an important role in all fields of society. The composition and quality of fiber determine its performance and price, and the continuity and integrity of fiber edge has great influence on the accuracy of fiber feature extraction, target separation, pattern recognition and computational blending ratio. Therefore, the edge detection of fiber image is a key link in the automatic fiber recognition system. However, fiber is disturbed by uneven illumination, focusing, noise and so on during embedding, slicing and sampling. It can not avoid the phenomenon of poor quality of micro fiber image, indistinct distinction between background area and target fiber, incomplete contour or adhesion. Moreover, the traditional edge detection algorithm can obtain the false and discontinuous edges of the micro fiber edges and can not effectively extract the edges of the adhesive fibers. In addition, the entry exit inspection and Quarantine Bureau, as an important organ of import and export inspection and verification, has been related to the detection of fiber components, that is, though it costs a lot of manpower and material resources, it can not achieve relatively accurate detection and verification. Therefore, it is a very meaningful topic to study the edge detection of micro fiber based on the computer digital image processing technology and the scientific grey system theory. This project is based on the National Natural Science Foundation of China "constraint based non negative matrix factorization algorithm and its application in automatic fiber recognition" (61472075). As in the textile, fiber and fabric on the subject at home and abroad have very high academic status and distinctive features of the University, our school has accumulated in cotton and chemical fiber research. This paper will explore the new field of image edge detection based on grey system theory and digital image processing technology of the combination of the extracted continuous, complete and accurate micro fiber edge as the core. Based on the grey system theory, NIBLACK algorithm and hole filling algorithm, a set of gray fiber system edge detection technology roadmap is proposed. The automatic detection platform system of micro fiber edge is developed. For each pixel in the image of micro fiber as the research object, the theory of grey system through the edge detection scheme based on GM (1,1) model and NIBLACK algorithm combining edge information obtained micro fiber and realize effective edge connection and then use the hole filling algorithm to handle false edges to extract the complete edge information. According to the design of micro fiber edge detection system based on grey system theory, starting from the principle of the algorithm makes full use of grey system theory in the system of academic research in China in a strong position and advanced level, play a grey system theory "less data poor information" model, showing the results of the design. The experimental results show that the algorithm can extract accurate and continuous complete microfiber edges.
【學(xué)位授予單位】：東華大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：N941.5;TP391.41

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