Mr. Fahad Mahmood Profile

Fahad Mahmood

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Proceedings Article | 13 April 2018 Paper

3D shape recovery from image focus using gray level co-occurrence matrix

Fahad Mahmood, Umair Munir, Fahad Mehmood, Javaid Iqbal

Proceedings Volume 10696, 1069628 (2018) https://doi.org/10.1117/12.2309446

KEYWORDS: 3D image processing, Image restoration, 3D acquisition, 3D modeling, Shape analysis, 3D applications, Cameras, 3D displays, Detection and tracking algorithms, Image acquisition

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Recovering a precise and accurate 3-D shape of the target object utilizing robust 3-D shape recovery algorithm is an ultimate objective of computer vision community. Focus measure algorithm plays an important role in this architecture which convert the color values of each pixel of the acquired 2-D image dataset into corresponding focus values. After convolving the focus measure filter with the input 2-D image dataset, a 3-D shape recovery approach is applied which will recover the depth map. In this document, we are concerned with proposing Gray Level Co-occurrence Matrix along with its statistical features for computing the focus information of the image dataset. The Gray Level Co-occurrence Matrix quantifies the texture present in the image using statistical features and then applies joint probability distributive function of the gray level pairs of the input image. Finally, we quantify the focus value of the input image using Gaussian Mixture Model. Due to its little computational complexity, sharp focus measure curve, robust to random noise sources and accuracy, it is considered as superior alternative to most of recently proposed 3-D shape recovery approaches. This algorithm is deeply investigated on real image sequences and synthetic image dataset. The efficiency of the proposed scheme is also compared with the state of art 3-D shape recovery approaches. Finally, by means of two global statistical measures, root mean square error and correlation, we claim that this approach –in spite of simplicity generates accurate results.

Proceedings Article | 13 April 2018 Paper

3D shape recovery from image focus using Gabor features

Fahad Mahmood, Jawad Mahmood, Ayesha Zeb, Javaid Iqbal

Proceedings Volume 10696, 106961F (2018) https://doi.org/10.1117/12.2309440

KEYWORDS: 3D image processing, Image restoration, Computer programming, 3D acquisition, Computer simulations, Image analysis, 3D displays, Shape analysis, Cameras, Image filtering

Read Abstract +

Recovering an accurate and precise depth map from a set of acquired 2-D image dataset of the target object each having different focus information is an ultimate goal of 3-D shape recovery. Focus measure algorithm plays an important role in this architecture as it converts the corresponding color value information into focus information which will be then utilized for recovering depth map. This article introduces Gabor features as focus measure approach for recovering depth map from a set of 2-D images. Frequency and orientation representation of Gabor filter features is similar to human visual system and normally applied for texture representation. Due to its little computational complexity, sharp focus measure curve, robust to random noise sources and accuracy, it is considered as superior alternative to most of recently proposed 3-D shape recovery approaches. This algorithm is deeply investigated on real image sequences and synthetic image dataset. The efficiency of the proposed scheme is also compared with the state of art 3-D shape recovery approaches. Finally, by means of two global statistical measures, root mean square error and correlation, we claim that this approach, in spite of simplicity, generates accurate results.

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