- Applications: Image Alignment

This papers presents an experience of specifying and implementing an XML format for text to image alignment at word and character level within the TEI framework. The format in question is a supplementary markup layer applied to heterogeneous transcriptions of medieval Latin and French manuscripts encoded using different “flavors” of the TEI (normalized for critical editions, diplomatic or palaeographic transcriptions). One of the problems that had to be solved was identifying “non-alignable” spans in various kinds of transcriptions. Originally designed in the framework of a research project on the ontology of letter-forms in medieval Latin and vernacular (mostly French) manuscripts and inscriptions, this format can be of use for all kinds of projects that involve fine-grain alignment of transcriptions with zones on digital images.

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Markerless Image Alignment Method for Pressure-Sensitive Paint Image

Sensors ◽

10.3390/s22020453 ◽

2022 ◽

Vol 22 (2) ◽

pp. 453

Author(s):

Kyosuke Suzuki ◽

Tomoki Inoue ◽

Takayuki Nagata ◽

Miku Kasai ◽

Taku Nonomura ◽

...

Keyword(s):

Computational Cost ◽

Measurement Data ◽

Image Alignment ◽

Feature Points ◽

Alignment Method ◽

Pressure Sensitive Paint ◽

Pressure Sensitive ◽

Difference Of Gaussian ◽

Tracing Algorithm ◽

The Difference

We propose a markerless image alignment method for pressure-sensitive paint measurement data replacing the time-consuming conventional alignment method in which the black markers are placed on the model and are detected manually. In the proposed method, feature points are detected by a boundary detection method, in which the PSP boundary is detected using the Moore-Neighbor tracing algorithm. The performance of the proposed method is compared with the conventional method based on black markers, the difference of Gaussian (DoG) detector, and the Hessian corner detector. The results by the proposed method and the DoG detector are equivalent to each other. On the other hand, the performances of the image alignment using the black marker and the Hessian corner detector are slightly worse compared with the DoG and the proposed method. The computational cost of the proposed method is half of that of the DoG method. The proposed method is a promising for the image alignment in the PSP application in the viewpoint of the alignment precision and computational cost.

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Survei Penelitian Pengenalan Pola dalam Identifikasi Biometrik

Jurnal Telekomunikasi dan Komputer ◽

10.22441/incomtech.v7i1.1162 ◽

2017 ◽

Vol 7 (1) ◽

pp. 19

Author(s):

Regina Lionnie ◽

Mudrik Alaydrus

Keyword(s):

Local Binary Pattern ◽

Image Alignment ◽

Chi Square ◽

Histogram Matching ◽

Gabor Features ◽

Averaging Filter

Pengenalan pola memainkan peranan yang penting dalam identifikasibiometrik. Hal ini dikarenakan pengenalan pola dalam identifikasibiometrik membantu pihak berwenang dalam mengungkap identitasseorang kriminal. Pengenalan pola identifikasi biometrik dalam imageprocessing mencakup pengenalan pola wajah, geometri dari sebuahtangan, iris dan retina dari organ mata, sklera mata, pembuluh darah,tanda kulit dan rambut tubuh. Pengenalan pola identifikasi biometrikmembutuhkan metode pengenalan pola yang akurat, pemilihan tahap praproses dan metode klasifikasi yang sesuai. Pada survei paper ini dibahasmengenai beberapa metode tahap pra proses seperti Averaging Filter,Histogram, Desaturation, Binerisation dan Image Alignment. Metodepengenalan pola yang dibahas pada paper ini adalah Gabor Features,Local Binary Pattern, Local Gabor Binary Pattern dan Haar WaveletTransform. Sedangkan metode klasifikasi yang dibahas adalah Euclideandistance, Chi-square distance dan Histogram Matching. Agar dapatmemberikan hasil terbaik, setiap sistem pengenalan pola tidak dapatmenggunakan metode yang sama untuk mengenali pola identifikasibiometrik yang berbeda. Dibutuhkan penelitian dalam penggunaanmetode pra proses, ekstraksi fitur dan klasifikasi untuk setiap identifikasibiometrik yang ingin dikenali polanya.

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