Automatic Segmentation and Inpainting of Specular Highlights for Endoscopic Imaging

Arnold, Mirko; Ghosh, Anarta; Ameling, Stefan; Lacey, Gerard

doi:10.1155/2010/814319

Cited by 85 publications

(93 citation statements)

References 38 publications

(63 reference statements)

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“…This unpredictable behaviour creates adverse conditions for image matching. Some applications that have to deal with reflections either segment, skip or interpolate these areas for dense image matching (Arnold et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Improving Image Matching by Reducing Surface Reflections Using Polarising Filter Techniques

Conen

Hastedt

Kahmen

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In dense stereo matching applications surface reflections may lead to incorrect measurements and blunders in the resulting point cloud.To overcome the problem of disturbing reflexions polarising filters can be mounted on the camera lens and light source. Reflections in the images can be suppressed by crossing the polarising direction of the filters leading to homogeneous illuminated images and better matching results.However, the filter may influence the camera's orientation parameters as well as the measuring accuracy. To quantify these effects, a calibration and an accuracy analysis is conducted within a spatial test arrangement according to the German guideline VDI/VDE 2634.1 (2002) using a DSLR with and without polarising filter. In a second test, the interior orientation is analysed in more detail. The results do not show significant changes of the measuring accuracy in object space and only very small changes of the interior orientation (c ≤ 4 µm) with the polarising filter in use.Since in medical applications many tiny reflections are present and impede robust surface measurements, a prototypic trinocular endoscope is equipped with polarising technique. The interior and relative orientation is determined and analysed. The advantage of the polarising technique for medical image matching is shown in an experiment with a moistened pig kidney. The accuracy and completeness of the resulting point cloud can be improved clearly when using polarising filters. Furthermore, an accuracy analysis using a laser triangulation system is performed and the special reflection properties of metallic surfaces are presented.

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Section: Introductionmentioning

confidence: 99%

Improving Image Matching by Reducing Surface Reflections Using Polarising Filter Techniques

Conen

Hastedt

Kahmen

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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show abstract

“…These threshold values are difficult to determine and are manually chosen in most methods. The proposed method provides an efficient way to detect the specularities based on the greyscale value as in (Arnold et al, 2010). Using a single threshold value, which is found after a preliminary testing of the method using a different RGB colour channel parameters on the human heart images from different patients, a threshold value has been set.…”

Section: Detection Of Specular Reflectionmentioning

confidence: 99%

“…Currently, the method used to correct specular reflection is based on the nearest pixels neighbouring the specular pixel, such as an iterative process to replace the specularities by the average of the nonspecular surrounding pixels (Greenspan et al, 2009), or, more recently, correction by the centroid colour of the pixels within a specific distance using filters (Arnold et al, 2010). However, these methods have the disadvantage of being computationally costly and lack practicality and applicability.…”

Section: Correction Of Specular Reflectionsmentioning

confidence: 99%

“…11. Different views of the 3D heart surface reconstruction (a) Original heart images with specular reflection (b) Proposed method (c) Inpainting algorithm (Arnold et al, 2010) …”

Section: Ajasmentioning

confidence: 99%

“…More recently, (Arnold et al, 2010) proposed an efficient method, which directly uses the RGB colour space for specular reflection segmentation based on median filtering and correction of the specularities based on an inpainting algorithm, which has given visually good results. This method proposes two modules to detect the different characteristics of specular reflections.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Three Dimensional Reconstruction of Human Heart Surface From Single Image- View Under Different Illumination Conditions

Al-Surmi

Rahmat

Dimon

et al. 2013

American Journal of Applied Sciences

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The 3D reconstruction from a single-view image is a longstanding issue in computer vision literature, especially in the medical field. Traditional medical imaging techniques that provide information about the heart and which are used to reconstruct the heart model, include Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images. However, in some cases, they are not available and the applications that use these techniques to model the human heart only produce acceptable results after a long process, which involves acquiring the input data, as well as the segmentation process, the matching process, effort and cost. Therefore, it would be useful to be able to use a 2D single image to reconstruct the 3D heart surface model. We introduce an image-based human heart surface reconstruction from a single image as input. To model the surface of the heart, the proposed method, first, detects and corrects the specular reflection from the heart's surface, which causes deformation of the surface in the R3. Second, it extrudes the three axes for each image pixel (e.g., x, y and z axes) from the input image, in which the z-axis is calculated using the intensity value. Finally, a 3D reconstruction of the heart surface is created to help the novice cardiac surgeon to reduce the period of time in learning cardiac surgery and to enhance their perception of the operating theatre. The experimental results for images of the heart show the efficiency of the proposed method compared to the existing methods.

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Effect of interpolation on specular reflections in texture‐based automatic colonic polyp detection

Kacmaz

Yılmaz

Aydın

2020

Int J Imaging Syst Tech

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Reflections of LED light cause unwanted noise effects called specular reflection (SR) on colonoscopic images. The aim of this study was to seek answers to the following two questions. (a) How are the texture features used in automatic detection of polyps affected by the interpolation on specular reflections? (b) If they are affected does it really affect the classification performance? In order to answer these questions, we used 610 colonoscopy images, and divided each image into tiles whose sizes were 32‐by‐32 pixels. From these tiles, we selected the ones without any specular reflection. We added different shape and size specular reflections cropped from real images onto the reflection‐free tiles. We then used the nearest neighbors, bilinear and bicubic interpolation techniques on the tiles on which SRs were added. On these tiles we extracted 116 texture features using 3 second‐order approaches, and 4 first‐order statistics. First, we used paired sample t test. Second, we performed automatic classification of polyps and background using random forest and k nearest neighbors (k‐NN) approaches using the texture features for different combinations of specular reflections added on the tiles from the polyp or background. The results showed that depending on the size of specular reflection, interpolation can cause a significant difference between the texture features that were coming from reflection‐free tiles and the same tiles on which interpolation was performed. In addition, we note that bicubic interpolation may be preferred to eliminate specular reflection when texture features are used for background and polyp discrimination.

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Automatic Segmentation and Inpainting of Specular Highlights for Endoscopic Imaging

Cited by 85 publications

References 38 publications

Improving Image Matching by Reducing Surface Reflections Using Polarising Filter Techniques

Improving Image Matching by Reducing Surface Reflections Using Polarising Filter Techniques

Three Dimensional Reconstruction of Human Heart Surface From Single Image- View Under Different Illumination Conditions

Effect of interpolation on specular reflections in texture‐based automatic colonic polyp detection

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