计算机工程与设计
計算機工程與設計
계산궤공정여설계
COMPUTER ENGINEERING AND DESIGN
2010年
5期
1060-1062,1092
,共4页
虹膜识别%独立成分分析%核向量机%支持向量机%最小包围球
虹膜識彆%獨立成分分析%覈嚮量機%支持嚮量機%最小包圍毬
홍막식별%독립성분분석%핵향량궤%지지향량궤%최소포위구
iris recognition%independent component analysis%core vector machines%support vector machines%minimum enclosing ball
针对虹膜识别过程中的特征提取及识别问题,提出了用独立成分分析提取虹膜特征,用核向量机进行识别的方法.从采集到的人眼图像中定位虹膜,并对其进行归一化处理和图像增强处理.用独立成分分析提取统计独立的特征,通过选择合适的特征个数可以达到较高的识别准确率.在得到虹膜特征编码后,用核向量机进行分类判决,核向量机是一种适合大规模数据集的快速支持向量机训练算法,并将结果与支持向量机的分类结果进行了对比.实验结果表明了该方法的可行性和有效性.
針對虹膜識彆過程中的特徵提取及識彆問題,提齣瞭用獨立成分分析提取虹膜特徵,用覈嚮量機進行識彆的方法.從採集到的人眼圖像中定位虹膜,併對其進行歸一化處理和圖像增彊處理.用獨立成分分析提取統計獨立的特徵,通過選擇閤適的特徵箇數可以達到較高的識彆準確率.在得到虹膜特徵編碼後,用覈嚮量機進行分類判決,覈嚮量機是一種適閤大規模數據集的快速支持嚮量機訓練算法,併將結果與支持嚮量機的分類結果進行瞭對比.實驗結果錶明瞭該方法的可行性和有效性.
침대홍막식별과정중적특정제취급식별문제,제출료용독립성분분석제취홍막특정,용핵향량궤진행식별적방법.종채집도적인안도상중정위홍막,병대기진행귀일화처리화도상증강처리.용독립성분분석제취통계독립적특정,통과선택합괄적특정개수가이체도교고적식별준학솔.재득도홍막특정편마후,용핵향량궤진행분류판결,핵향량궤시일충괄합대규모수거집적쾌속지지향량궤훈련산법,병장결과여지지향량궤적분류결과진행료대비.실험결과표명료해방법적가행성화유효성.
To solve the feature extraction problem and recognition problem in the process of iris recognition, an algorithm is proposed, which adopts independent component analysis to extract iris feature and core vector machines to recognize. Normalization and image enhancement is used to process the iris position which is located in the eye images. Independent component analysis is used to extract statistical independent feature and a good result will be received by selecting right feature numbers. The core vector machine is used to classify the iris feature and it can handle large data sets more quickly by compared to support vector machines. Experimental results show that the algorithm is feasible and suitable for iris recognition.
