The identification through biometric is a better way because it associate with individual not with information passing from one place to another. There are numerous biometric measures which can be used to help derive an individual identity. It is the biometric process and has many advantages over other biometric traits such as face, iris, fingerprint, palm print, etc. Most current approaches make the unrealistic assumption that persons walk along a fixed direction or a pre-defined path. Gait is the manner or style of moving on foot. Human Gait recognition identifies the individuals by the way in which they walk. Recognition of an individual is an important task to identify people. A gait sequence is collected from arbitrary walking directions. In this paper we present the approach of human identity and gender recognition using Model based features extraction and SURF for matching along with SVM and MDA algorithm.
Punjab is the state that contributes the most food grains to the central pool and is mostly an agricultural state. Small and marginal farmers are the backbone of Indian agriculture. Majority of the holdings are medium and number of such holdings are increasing with fragmentation of land. So, the present study was conducted with the objective of studying the socio-economic characteristics of the respondents. Data were collected from Pathankot and Gurdaspur district of Punjab. Two blocks was selected from each district and from total four blocks 25 respondents were selected randomly to make sample size of 100 respondents. It was found that vast proportion of respondents belonged to old age category. Youth is moving abroad and showing less interest in agriculture sector. Significant percentage of respondents (49 percent) were found to have attained schooling up to matric level and most of the respondents belong to nuclear family. It was found that though having good farming experience and education level, farmers of the state were not sticking to the recommended practices and resource use levels. The information of operational landholding of the respondents was classified into Small, Semi- medium, Medium and Large categories and mostly respondents have medium landholding i.e. 4-10 acre of land. The findings also revealed that respondents who attended more training and had more extension contacts have high knowledge level regarding paddy straw management.
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