MERI-Journal of Management & IT

Padma Mishra ¹, Anup Girdhar ¹

Affiliations
1 Department of Computer Science, TMV University, Pune, IN

Abstract

On Road Obstacles detection from moving camera is also come under object detection. Road obstacles are a source of serious accidents that have a simple influence on driver safety, traffic flow efficiency and damage of the vehicle. The obstacle detection technologies are increasingly popular choices for driver assistant system. Obstacles detection is essential to avoid such kind of the accidents. Determining obstacles is very difficult and also it becomes complicated because of various problems like existence of shadow, environmental variations or an unexpected act of any moving things (e.g., car overtaking, animal coming) and many others with stationary camera. A new process is presented for detecting obstacles from moving camera and moving objects which overcomes numerous limitations above stationary cameras and moving/stationary objects. Further, paper analyses latest research developments to spot obstacles for moving cameras and moving objects with discussion of key points and limitations of each approach. Given the importance of obstacle detection, the main measure of interest was to decrease the road accidents and driver's safety. Detection of obstacles with moving camera and moving objects is more robust and reliable than stationary cameras.

Keywords

Obstacle Detection, Intelligent Transportation System, Driver Safety.

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Padma Mishra ¹, Anup Girdhar ¹

Affiliations
1 Department of Computer Science, TMV University, Pune, IN

Abstract

Moving vehicle detection remain very critical and thus intended for Video-based solution, comparing to other techniques and by considering the traffic video sequence recorded from a video camera, this paper presents a video-based solution applied with adaptive subtracted background technology in combination with virtual detector and blob tracking technologies. This paper provides Experimental results moving vehicle detection which is implemented in Visual C++ code with OpenCV, thus the proposed method used for detection.

Keywords

Computer Vision, GMM, ITS, Open CV, Vehicle Detection.

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Padma Mishra ¹, Anup Girdhar ¹

Affiliations
1 Department of Computer Science, TMV University, Pune, IN

Abstract

Image of particular object as vehicle as image detection is mainly the important role in driver assistant system as well as in intelligent autonomous vehicles. Thus in real - time it run time performance in term of accuracy performance. Thus the proposed system is discussed with consideration of overlapping of one image with another and partial view of images etc.thus the partial vehicle detection module is basically on driver assistant system and intelligent auto-nous vehicles by considering what type of image as vehicle appears in which area should extracted and classification based color Histogram of Orientated Gradients. Thus it perform the conversion of the input image as vehicle into gray image then Supreme stable outer region thus extract input as stable object in the previous output with the use of more one or more frames. In upcoming research the support vector machine retrieve the image as data from maximum stable external region result and then matches with database of image. Thus the concurrently the fuzzy pattern cluster techniques retrieve the object of interest from SSOR result and then apply the colors after that it will matches it with existing database images of vehicles.

Keywords

Histogram of Orientated Gradients, Support Vector Machine, Fuzzy.

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Padma Mishra ¹, Vaishali B. ¹, Sangvikar

Affiliations
1 P.E.S's Modern College of Engineering, Pune, IN

Abstract

The emerging fields of academic analytics also the educational data mining are rapidly producing new hypothesis for gathering, analyzing, and presenting student data. Different Area of Computer applications and also business administrations have addition significant standing value in higher education. Thus the kind of education, students turn in these areas depends on the geo-economical and the social demography. Thus the decision making of an institution in these area of higher education dependent on several factors like economic condition of students, geographical area of the institution, quality of educational organizations etc. To have a strategic move for the development of importing knowledge in this area requires understanding the behavior aspect of these parameters. Thus the scientific apprehension of these can be had from obtaining patterns or recognizing the attribute behavior from early academic years. Farther, applying data mining tool to the preceding data on the attributes known will throw better light on the behavioral view of identified patterns.

Keywords

Data Mining, Decision Tree Classification, Educational Data Mining.

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Padma Mishra ¹, Vaishali B. Sangvikar ¹

Affiliations
1 MCA Department, P.E.S's Modern College of Engineering, Pune, IN

Abstract

Now a student’s performance towards education is influenced through various factor. Proper motivation and guidance towards Students should increase. Factor and proper assessment abilities support for better performance. Thus the different techniques of data mining is used for increase the performances of the candidates. Identifying the performance of candidates most important research area .studies of educational data mining based on distinguish mining algorithms connected with different predictions techniques. Thus learners performance is suffered by distinguish parameters for example considers a learning environment, financial issues etc. the paper study based on environmental factors and institute factors for evaluating student performance.

Keywords

Data Mining, Educational Data Mining, Classification.

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