ICTACT Journal on Image and Video Processing

Surya Kasturi ¹, Ashoka Vanjare ², S. N. Omkar ²

Affiliations
1 Department of Electronics and Communication Engineering, Marri Laxman Reddy Institute of Technology and Management, IN
2 Department of Aerospace Engineering, Indian Institute of Science, IN

Abstract

Face recognition plays an important role in surveillance, biometrics and is a popular application of computer vision. In this paper, color based skin segmentation is proposed to detect faces and is matched with faces from the dataset. The proposed color based segmentation method is tested in different color spaces to identify suitable color space for identification of faces. Based on the sample skin distribution a Multivariate Gaussian Model is fitted to identify skin regions from which face regions are detected using connected components. The detected face is match with a template and verified. The proposed method Multivariate Gaussian Model - Fisher Linear Discriminative Analysis (MGM - FLDA) is compared with machine learning - Viola&Jones algorithm and it gives better results in terms of time.

Keywords

Face Recognition, Multivariate Gaussian Model, Image Segmentation, Connected Component, Color Spaces.

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S. N. Omkar ¹, Amarjot Singh ²

Affiliations
1 Department of Aerospace Engineering, Indian Institute of Science, Bangalore, IN
2 Department of Electrical and Electronics Engineering, National Institute of Technology, Warangal, IN

Abstract

Carpal Tunnel Syndrome also known as median neuropathy is a painful disorder of the wrist and hand. It is a medical condition arising due to the abbreviation of the median nerve in the vicinity of carpal tunnel, resulting in numbness, parenthesis and muscle weakness in hand. We present an effective optical approach for the measurement of strain on superficial muscles and tendons due to wrist extension, a remedy for carpal tunnel syndrome. The DIC code developed computes the in-plane strain with a correlation function using pictures taken, using a CCD camera, before and after extension. The shift between the initial picture and subsequent one is performed by computation of cross-correlation using FFT. This study can assist practitioners working in the field of applied anthropology to develop advanced diagnosis methodologies.

Keywords

Digital Image Correlation, Carpal Tunnel Syndrome, Wrist Extension.

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S. N. Omkar ¹, M. Monisha ²

Affiliations
1 Department of Aerospace Engineering, Indian Institute of Science, Bangalore, Karnataka, IN
2 Department of Information Technology, National Institute of Technology Karnataka, Surathkal, IN

Abstract

In the recent years many approaches have been made that uses computer vision algorithms to interpret sign language. This endeavour is yet another approach to accomplish interpretation of human hand gestures. The first step of this work is background subtraction which achieved by the Euclidean distance threshold method. Thinning algorithm is then applied to obtain a thinned image of the human hand for further analysis. The different feature points which include terminating points and curved edges are extracted for the recognition of the different signs. The input for the project is taken from video data of a human hand gesturing all the signs of the American Sign Language.

Keywords

Hand Gesture Recognition, Sign Language, Pre-Processing, Thinning Algorithm, Feature Points Extraction.

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Amarjot Singh ¹, S. N. Omkar ²

Affiliations
1 Department of Electrical and Electronics Engineering, National Institute of Technology, Warangal, IN
2 Department of Aerospace Engineering, Indian Institute of Science, Bangalore, IN

Abstract

Tarsal tunnel syndrome (TTS), also known as posterior tibial neuralgia is a painful disorder of the foot. It is a medical condition arising due to the compression of the tibial nerve in the tarsal tunnel, resulting in numbness, parenthesis and muscle weakness in foot. A number of imaging methodologies such as ultrasound as well as MRI imaging has been used in the past in order to analyze the strain pattern of gastrocnemius tendon and aponeurosis from the surface of the skin without analyzing the internal tendons. The DIC code developed, computes the in-plane strain with a correlation function using pictures taken before and after stretching, using a CCD camera. The shift between the initial picture and subsequent one is evaluated by cross-correlation using FFT. This paper gives in detail description of the preprocessing steps necessary to extract Zone of Interest from the two images. The effects of stretching on the superficial components of the tibial nerve, the posterior tibial artery and vein, and the tibialis posterior, flexor digitorum longus and flexor hallucis longus tendons in the calf and foot are studied.

Keywords

Tarsal Tunnel Syndrome, Image Correlation, Fast Fourier Transform, Strain Analysis, Cross Correlation, Tibialis Posterior, Flexor Digitorum Longus, Flexor Hallucis Longus Tendons.

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