Rectification and recognition of text in 3-D scenes

Myers, Gregory; Bolles, Robert C.; Luong, Quang-Tuan; Herson, James A.; Aradhye, Hrishikesh B.

doi:10.1007/s10032-004-0133-4

Cited by 56 publications

(42 citation statements)

References 14 publications

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“…In literature, the homographic transformation estimation from text images is used in document analysis [15], [23] and natural scene text recognition systems [5], [14], [18], [19]. Documents used in document analysis systems usually have multiple lines and these lines are used to extract the homographic transformation.…”

Section: Text-based Homographic Transformation Estimationmentioning

confidence: 99%

“…Methods introduced in [5], [19] impose restrictions in determining the homographic transformation. For example, [5] reduces the homographic to affine transformation and [19] assumes that only the horizontally parallel lines can have vanishing points and vertically parallel lines stay almost parallel in the taken image. The methods presented in [14], [18] can estimate the homographic transformation in general.…”

Section: Text-based Homographic Transformation Estimationmentioning

confidence: 99%

See 1 more Smart Citation

Precise Vehicle Speed Measurement Based on a Hierarchical Homographic Transform Estimation for Law Enforcement Applications

Eslami

Raie

Faez

2016

IEICE Trans. Inf. & Syst.

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SUMMARYToday, computer vision is used in different applications for intelligent transportation systems like: traffic surveillance, driver assistance, law enforcement etc. Amongst these applications, we are concentrating on speed measurement for law enforcement. In law enforcement applications, the presence of the license plate in the scene is a presupposition and metric parameters like vehicle's speed are to be estimated with a high degree of precision. The novelty of this paper is to propose a new precise, practical and fast procedure, with hierarchical architecture, to estimate the homraphic transform of the license plate and using this transform to estimate the vehicle's speed. The proposed method uses the RANSAC algorithm to improve the robustness of the estimation. Hence, it is possible to replace the peripheral equipment with vision based systems, or in conjunction with these peripherals, it is possible to improve the accuracy and reliability of the system. Results of experiments on different datasets, with different specifications, show that the proposed method can be used in law enforcement applications to measure the vehicle's speed. key words: feature extraction, RANSAC estimator, license plate, speed measurement, law enforcement

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Section: Text-based Homographic Transformation Estimationmentioning

confidence: 99%

Section: Text-based Homographic Transformation Estimationmentioning

confidence: 99%

Precise Vehicle Speed Measurement Based on a Hierarchical Homographic Transform Estimation for Law Enforcement Applications

Eslami

Raie

Faez

2016

IEICE Trans. Inf. & Syst.

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“…Another topic of rising interest is reading text in videos, including road signs from car-mounted cameras [137,138,139,140]. Such text is often in color and exhibits more geometric and photometric distortion than text scanned from paper.…”

Section: Cameras and Displaysmentioning

confidence: 99%

Adaptive and Interactive Approaches to Document Analysis

Nagy¹,

Veeramachaneni

2008

Machine Learning in Document Analysis and Recognition

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Summary. This chapter explores three aspects of learning in document analysis: (1) field classification, (2) interactive recognition, and (3) portable and networked applications. Context in document classification conventionally refers to language context, i.e., deterministic or statistical constraints on the sequence of letters in syllables or words, and on the sequence of words in phrases or sentences. We show how to exploit other types of statistical dependence, specifically the dependence between the shape features of several patterns due to the common source of the patterns within a field or a document. This type of dependence leads to field classification, where the features of some patterns may reveal useful information about the features of other patterns from the same source but not necessarily from the same class. We explore the relationship between field classification and the older concepts of unsupervised learning and adaptation. Human interaction is often more effective interspersed with algorithmic processes than only before or after the automated parts of the process. We develop a taxonomy for interaction during training and testing, and show how either human-initiated and machine-initiated interaction can lead to human and machine learning. In a section on new technologies, we discuss how new cameras and displays, web-wide access, interoperability, and essentially unlimited storage provide fertile new approaches to document analysis.

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“…A very effective solution to text-pose estimation is based on finding vanishing points of text lines (Clark & Mirmehdi, 2002a;Myers et al, 2001). This type of knowledge-based approach has to impose restrictions on text layout (a minimum number of lines must be present, of sufficient length, with consistent paragraph justification) and the search for vanishing points is computationally expensive.…”

Section: Approaches To Text-pose Estimationmentioning

confidence: 99%