Informatics Publishing Limited

Sanjay Kumar ¹, Padmavati ¹, Anirudh Chaudhary ¹, Preeti Sharma ²

Affiliations
1 Department of Psychology Chaudhary Charan Singh University Meerut, U. P., IN
2 Department of Psychology R. G. P. G. College Meerut, U. P., IN

Abstract

The present study aims to study the psycho-social causes of traumatic experiences in a women's life of different age groups. For this purpose 175 girls and women of age range 20 to 60 years of age were interviewed for the study. These subjects were divided into three groups; they were 20-25 Yrs., 35-40 Yrs. and 50-55 years of age. These subjects were contacted individually and open ended questions were asked. The questions were related to their opinion and attitude towards causes of traumatic incidents occurring with them. The issues considered during interview were deterioration of social values, poor parenting, modernization, nuclearization of families, poor schooling, poor interpersonal bonds, sexual behavior, poor social responsibility, freedom of expression for love and sex, etc. The content analysis of obtained data was done by two experts to maintain the consistent validity of the analysis of the data. Percentage was used for further interpretation and presentation of results. Obtained results indicated some significant causes of trauma against women most often existing in our society. It was also obtained that different age groups vary qualitatively in the causes of traumatic experiences with them caused by male counterpart.

Keywords

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Rahul Prakash ¹, Padmavati ¹

Affiliations
1 PEC University of Technology, Chandigarh, IN

Abstract

SIFT algorithm is one of the most notable algorithm being used for feature extraction. In order to detect the object, these extracted features should be matched with the features extracted from the target image. For the matching purpose there are number of algorithms (Euclidian distance, Cityblock, correlation etc) to compute the distance between extracted features. But the space and time complexity of this algorithm is high enough to meet the real time requirements because of having the large feature vector space (256¹²⁸). To overcome this drawback, Binary-SIFT is introduced by Kadir A. Peker having a very small feature vector space (comparatively) and meets the real time requirements by using the XOR function for matching purpose which needs very less time in comparison with the technique mentioned above. In this paper we have done the performance evaluation of SIFT and Binary-SIFT on test images of Indian face database and The ORL Database of Faces. The performance of both the algorithms is same if the variation (change in scale, illumination and rotation) in the image is very low. But as the variation increases the Binary-SIFT algorithm began to lack the performance in comparison with SIFT.

Keywords

Binary-SIFT, DoG (Difference of Gaussian), Keypoints, SIFT, XOR.

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