Improved Fingerprint Recognition Algorithm Application Study on Smart Home

2013 ◽  
Vol 734-737 ◽  
pp. 2970-2973
Author(s):  
Shu Qian Chen ◽  
Yang Lie Fu ◽  
Ming Yang Yin

Study on a new type of fingerprint identification algorithm and its application in intelligent home electric control lock problem. The traditional fingerprint recognition algorithms on fingerprint minutiae matching accuracy is low, difficult to accurately extract details, leading to lock malfunction or could not be opened. In order to overcome this problem, improved Point pattern fingerprint recognition matching algorithm, joined the matching weight coefficient on the base of pattern matching algorithm, and gives the hardware structure of fingerprint identification system, the improved algorithm is successfully applied in smart home applications, the example shows that, the improved algorithm can effectively improve the recognition rate , reduce false positives, has a certain practical value.

2012 ◽  
Author(s):  
Wan Azizun Wan Adnan ◽  
Tze Siang Lim ◽  
Salasiah Hitam

Teknik cetak ibujari merupakan satu daripada teknologi biometrik yang paling boleh diharapkan. Beberapa pendekatan terhadap pemadanan ibujari secara automatik telah dicadangkan dalam saranan. Dalam pengecaman ibujari, pra–prosesan seperti pelicin, binarization dan thinning diperlukan. Kemudian, ciri–ciri cetak ibujari yang terperinci diambil berdasarkan algoritma pengecaman cetak ibujari (seperti dengan menggunakan Fast Fourier Transform (FFT)) mungkin memerlukan teknik–teknik pengkomputeran yang banyak sehingga menjadikannya tidak praktikal. Algoritma berdasarkan wavelet mungkin merupakan kunci untuk membina sistem pengecaman cetak ibujari kos rendah yang boleh dioperasi dalam sistem komputer bermodul kecil. Di sini, satu sistem pengecaman cetak ibujari yang boleh menjalankan pemadanan cetak ibujari berdasarkan kepada ciri–ciri yang diperolehi daripada domain jelmaan wavelet diperkenalkan. Kajian ini adalah berdasarkan kepada perisian MATLAB dan aplikasinya dalam toolbox seperti Wavelet and Image Processing Toolbox. Kata kunci: Biometrik, wavelet, cetaksekuriti, pengecaman cetak ibujari Fingerprint technique is one of the most reliable biometric technologies. In the fingerprint recognition, pre-processing such as smoothing, binarization, and thinning are needed. Then, fingerprint minutia feature is extracted. Some fingerprint identification algorithm (such as using Fast Fourier Transform, (FFT)) may require so much computation as to be impractical. Wavelet based algorithm may be the key to making a low cost fingerprint identification system that would operate on a small computer. We present a fingerprint recognition system that can match the fingerprint images based on features extracted in the wavelet transform domain. This study is implemented based on MATLAB Software and their toolbox applications, such as Wavelet and Image Processing Toolbox. Key words: Biometrics, wavelet, security, fingerprint recognition


2011 ◽  
Vol 1 ◽  
pp. 97-101
Author(s):  
Hong Sun

The automated fingerprint identification algorithm has high time and space complexity in the embedded system. How to reduce the complexity is one of the hot research topics. The process of fingerprint identification and choice of algorithm platform are analyzed in the paper. Design of embedded fingerprint identification hardware system based on DSP, including the selection of microprocessor and fingerprint sensor and the communication between them, is introduced in detail. In additional, main software composition and flow are explained. At last, serial peripheral interface communication is simulated.


2011 ◽  
Vol 135-136 ◽  
pp. 739-742
Author(s):  
Jin Hai Zhang

Fingerprint recognition has wide application prospect in all fields which contain identity authentication. Construction of accurate and reliable,safe and Practical automatic fingerprint identification system(AFIS) has become researc hotspot. Although theoretical research and application developmen of AFIS have got a significant Progress,accuracy of the algorithm and proeessing speeds till need to be improved. In this paper, fingerprint image preprocessing algorithms,fingerprint singular Points and minutiae extraction algorithm and fingerprint matching algorithm are analyzed and discussed in detail.


Author(s):  
Kalaivani Subramani ◽  
Shantharajah Periyasamy ◽  
Padma Theagarajan

Background: Agriculture is one of the most essential industry that fullfills people’s need and also plays an important role in economic evolution of the nation. However, there is a gap between the agriculture sector and the technological industry and the agriculture plants are mostly affected by diseases, such as the bacterial, fungus and viral diseases that lead to loss in crop yield. The affected parts of the plants need to be identified at the beginning stage to eliminate the huge loss in productivity. Methods: In the present scenario, crop cultivation system depend on the farmers experience and the man power, but it consumes more time and increases error rate. To overcome this issue, the proposed system introduces the Double Line Clustering technique based disease identification system using the image processing and data mining methods. The introduced method analyze the Anthracnose, blight disease in grapes, tomato and cucumber. The leaf images are captured and the noise has been removed by non-local median filter and the segmentation is done by double line clustering method. The segmented part compared with diseased leaf using pattern matching algorithm. Methods: In the present scenario, crop cultivation system depend on the farmers experience and the man power, but it consumes more time and increases error rate. To overcome this issue, the proposed system introduces the Double Line Clustering technique based disease identification system using the image processing and data mining methods. The introduced method analyze the Anthracnose, blight disease in grapes, tomato and cucumber. The leaf images are captured and the noise has been removed by non-local median filter and the segmentation is done by double line clustering method. The segmented part compared with diseased leaf using pattern matching algorithm. Conclusion: The result of the clustering algorithm achieved high accuracy, sensitivity, and specificity. The feature extraction is applied after the clustering process which produces minimum error rate.


2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Uttam U. Deshpande ◽  
V. S. Malemath ◽  
Shivanand M. Patil ◽  
Sushma. V. Chaugule

2016 ◽  
Vol 17 (8) ◽  
pp. 766-780 ◽  
Author(s):  
Yun-xiang Zhao ◽  
Wan-xin Zhang ◽  
Dong-sheng Li ◽  
Zhen Huang ◽  
Min-ne Li ◽  
...  

2011 ◽  
Vol 271-273 ◽  
pp. 1509-1513 ◽  
Author(s):  
Mei Xiu Lu ◽  
Fu Rong Wang ◽  
Feng Li

Image thinning is one of important steps of fingerprint preprocessing. Most of fingerprint recognition algorithms checked the characteristic points on thinning image. In this paper, we discover some shortages in OPTA and mathematical morphology thinning algorithm and find out the reasons for some shortages such as many glitches and snags, defective thinning, and so on. A new improved algorithm is proposed in the paper, which is an ideal algorithm because it is faster, produces less glitch, and thins completely.


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