基于虛擬樣本的改進(jìn)人臉識別算法研究及應(yīng)用
發(fā)布時間：2018-12-14 12:33
【摘要】：針對實(shí)際采集的視頻中背景復(fù)雜,人物多變,圖像處理時間長,訓(xùn)練樣本不足的問題,提出了構(gòu)造虛擬樣本,并結(jié)合Gabor濾波器及對PCA-LDA算法加以改進(jìn)的人臉識別算法,以應(yīng)用于教室點(diǎn)名系統(tǒng)。首先對教室采集到的視頻進(jìn)行裁剪,按幀截取并檢測出含有人臉的部分圖像并單獨(dú)保存為測試圖像,然后將其與已有人臉庫里的訓(xùn)練圖像進(jìn)行對比,最后采用提出的鏡像法構(gòu)造虛擬樣本,并結(jié)合了Gabor濾波器以及PCNN灰度圖像增強(qiáng)處理算法的改進(jìn)PCA-LDA算法進(jìn)行人臉識別。仿真實(shí)驗(yàn)表明,提出的算法預(yù)測了樣本可能存在的變化,也在一定程度上降低了計算復(fù)雜度,明顯地提高了識別率,并在教室點(diǎn)名系統(tǒng)中得到了較好的驗(yàn)證。
[Abstract]:Aiming at the problems of complex background, changeable characters, long image processing time and insufficient training samples, a new face recognition algorithm based on Gabor filter and PCA-LDA algorithm is proposed. To apply to the classroom roll call system. First of all, the video collected in the classroom is clipped, the part of the face image is captured and detected according to the frame, and stored separately as the test image, and then it is compared with the training image in the existing human face database. Finally, the proposed image method is used to construct the virtual sample, and the improved PCA-LDA algorithm, which combines the Gabor filter and the PCNN gray image enhancement algorithm, is used for face recognition. The simulation results show that the proposed algorithm can predict the possible changes of the samples, reduce the computational complexity to a certain extent, and improve the recognition rate obviously, and is well verified in the classroom-roll call system.
【作者單位】： 江南大學(xué)物聯(lián)網(wǎng)工程學(xué)院;
【基金】：國家自然科學(xué)基金(No.61672265) 江蘇省產(chǎn)學(xué)研聯(lián)合創(chuàng)新資金項目(No.BY2013015-35)
【分類號】：TP391.41
[Abstract]:Aiming at the problems of complex background, changeable characters, long image processing time and insufficient training samples, a new face recognition algorithm based on Gabor filter and PCA-LDA algorithm is proposed. To apply to the classroom roll call system. First of all, the video collected in the classroom is clipped, the part of the face image is captured and detected according to the frame, and stored separately as the test image, and then it is compared with the training image in the existing human face database. Finally, the proposed image method is used to construct the virtual sample, and the improved PCA-LDA algorithm, which combines the Gabor filter and the PCNN gray image enhancement algorithm, is used for face recognition. The simulation results show that the proposed algorithm can predict the possible changes of the samples, reduce the computational complexity to a certain extent, and improve the recognition rate obviously, and is well verified in the classroom-roll call system.
【作者單位】： 江南大學(xué)物聯(lián)網(wǎng)工程學(xué)院;
【基金】：國家自然科學(xué)基金(No.61672265) 江蘇省產(chǎn)學(xué)研聯(lián)合創(chuàng)新資金項目(No.BY2013015-35)
【分類號】：TP391.41
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