Matchability Prediction for Full-Search Template Matching Algorithms

Peñate-Sánchez, Adrián; Porzi, Lorenzo; Moreno-Noguer, Francesc

doi:10.1109/3dv.2015.47

Cited by 11 publications

(7 citation statements)

References 29 publications

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“…It is important to note that if a better version of the PG collection is adopted, the matching process will not be repeated. Advances in image processing and computer vision techniques such as template matching (Penate-Sanchez et al , 2015), allow for the automatic detection of similar scanned pages and the updating of matching JSON files (Figure 7).…”

Section: Discussionmentioning

confidence: 99%

Semantic enrichment on large scanned collections through their “satellite texts”: the paradigm of Migne’s Patrologia Graeca

Varthis

Tzanavaris

Giarenis

et al. 2021

IDD

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Purpose This paper aims to present a methodology for the semantic enrichment on the scanned collection of Migne’s Patrologia Graeca (PG), attempting to easily locate on the Web domain the scanned PG source, when a reference of this source is described and commented on another scanned or textual document, and to semantically enrich PG through related scanned or textual documents named “satellite texts” published by third people. The present enrichment of PG uses as satellite texts the Dorotheos Scholarios's Synoptic Index (DSSI) which act as metadata for PG. Design/methodology/approach The methodology consists of two parts. The first part addresses the DSSI transcription via a proper web tool. The second part is divided into two subsections: the accomplishment of interlinking the printed column numbers of each scanned PG page with its actual filename, which is the build of a matching function, and the build of a web interface for PG, based on the generated Uniform Resource Identifiers (URIs) of the above first subsection. Findings The result of the implemented methodology is a Web portal, capable of providing server-less search of topics with direct (single click) navigation to sources. The produced system is static, scalable, easy to be managed and requires minimal cost to be completed and maintained. The produced data sets of transcribed DSSI and the JavaScript Object Notation (JSON) matching functions are available for personal use of students and scholars under Creative Commons license (CC-BY-NC-SA). Social implications Scholars or anyone interested in a particular subject can easily locate topics in PG and reference them, using URIs that are easy to remember. This fact contributes significantly to the related scientific dialogue. Originality/value The methodology uses the transcribed satellite texts of DSSI, which act as metadata for PG, to semantically enrich PG collection. Furthermore, the built PG Web interface can be used by other satellite texts as a reference basis to further enrich PG, as it provides a direct identification of sources. The presented methodology is general and can be applied to any scanned collection using its own satellite texts.

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Section: Discussionmentioning

confidence: 99%

Semantic enrichment on large scanned collections through their “satellite texts”: the paradigm of Migne’s Patrologia Graeca

Varthis

Tzanavaris

Giarenis

et al. 2021

IDD

View full text Add to dashboard Cite

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“…However, it did not address the issue of landmark selection, nor did it consider natural characteristics and environmental changes. Penate-Sanchez et al [23] used a neural network to predict the matchability of a template for solving a panorama-stitching problem of natural scenery.…”

Section: Related Workmentioning

confidence: 99%

Deep Neural Network-Based Landmark Selection Method for Optical Navigation on Lunar Highlands

et al. 2020

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Spacecraft that rely on self-localization based on optical terrain images require suitable landmark information along their flight paths. When navigating within the vicinity of the moon, a lunar crater is an intuitive choice. However, in highland areas or regions having low solar altitudes, craters are less reliable because of heavy shadowing, which results in infrequent and unpredictable crater detections. This paper, therefore, presents a method for suggesting navigation landmarks that are usable, even with unfavorable illumination and rough terrain, and it provides a procedure for applying this method to a lunar flight plan. To determine a good landmark, a convolutional neural network (CNN)-based object detector is trained to distinguish likely landmark candidates under varying lighting geometries and to predict landmark detection probabilities along flight paths attributable to various dates. Dates having more favorable detection probabilities can be determined in advance, providing a useful tool for mission planning. Numerical experiments show that the proposed landmark detector generates usable navigation information at sun elevations of less than 1.8 • in highland areas.

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“…There are two ways to reduce the running time of the template matching algorithm: One is to decrease the cost of computing in each matching point, and the other is to narrow the search area. In the traditional matching method, such as full-search template matching (FSTM) [32], a large number of search areas are invalid, causing a heavy computational cost. In order to reduce the unnecessary computational time of the template matching in whole video sequences, an effective measure reducing the search area is also very significant.…”

Section: Search Area Selectionmentioning

confidence: 99%

Generating a Cylindrical Panorama from a Forward-Looking Borehole Video for Borehole Condition Analysis

et al. 2019

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Geological exploration plays a fundamental and crucial role in geological engineering. The most frequently used method is to obtain borehole videos using an axial view borehole camera system (AVBCS) in a pre-drilled borehole. This approach to surveying the internal structure of a borehole is based on the video playback and video screenshot analysis. One of the drawbacks of AVBCS is that it provides only a qualitative description of borehole information with a forward-looking borehole video, but quantitative analysis of the borehole data, such as the width and dip angle of fracture, are unavailable. In this paper, we proposed a new approach to create a whole borehole-wall cylindrical panorama from the borehole video acquired by AVBCS, which provides a possibility for further analysis of borehole information. Firstly, based on the Otsu and region labeling algorithms, a borehole center location algorithm is proposed to extract the borehole center of each video image automatically. Afterwards, based on coordinate mapping (CM), a virtual coordinate graph (VCG) is designed in the unwrapping process of the front view borehole-wall image sequence, generating the corresponding unfolded image sequence and reducing the computational cost. Subsequently, based on the sum of absolute difference (SAD), a projection transformation SAD (PTSAD), which considers the gray level similarity of candidate images, is proposed to achieve the matching of the unfolded image sequence. Finally, an image filtering module is introduced to filter the invalid frames and the remaining frames are stitched into a complete cylindrical panorama. Experiments on two real-world borehole videos demonstrate that the proposed method can generate panoramic borehole-wall unfolded images from videos with satisfying visual effect for follow up geological condition analysis. From the resulting image, borehole information, including the rock mechanical properties, distribution and width of fracture, fault distribution and seam thickness, can be further obtained and analyzed.

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Matchability Prediction for Full-Search Template Matching Algorithms

Cited by 11 publications

References 29 publications

Semantic enrichment on large scanned collections through their “satellite texts”: the paradigm of Migne’s Patrologia Graeca

Semantic enrichment on large scanned collections through their “satellite texts”: the paradigm of Migne’s Patrologia Graeca

Deep Neural Network-Based Landmark Selection Method for Optical Navigation on Lunar Highlands

Generating a Cylindrical Panorama from a Forward-Looking Borehole Video for Borehole Condition Analysis

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