A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Chopade, P. B.
- Machine Vision based Front Vehicle Detection Algorithm
Authors
1 M. E. S. College of Engineering, Pune- 411001, IN
2 M. E. S. College of Engineering, Pune-411001, IN
Source
Digital Image Processing, Vol 7, No 9 (2015), Pagination: 278-281Abstract
Most common approaches of vehicle detection are using active sensor such as radar based, laser based and acoustic based. The second approach for vehicle detection is using optical sensor (camera), which is cost effective and robust one. This paper present vision based preceding vehicle detection algorithm. The features of front vehicle are extracted using edge detection. Blob analysis is utilized herein to locate position of the vehicle. To maintain safe distance between the two vehicles, algorithm also provides the longitudinal distance information. Driver can be getting alerted if distance is less than the safe range. With the help of this algorithm collision between the two vehicles can be avoided. The experimental results show that the detection rate is above 80%.Keywords
Vehicle Detection, Morphological Edge Detection, Blob Analysis.
- Low-Complexity Based Modified Image Super-Resolution Scheme by the Design of Dyadic Integer Coefficient Based Wavelet Filters
Authors
1 Modern Education Society’s College of Engineering, Pune-01, IN
2 KJ’s Educational Institute, Pune-1, IN
Source
Digital Image Processing, Vol 7, No 4 (2015), Pagination: 120-124Abstract
This paper presents a low-complexity based modified image super-resolution scheme based on the wavelet coefficients soft-thresholding .The design this scheme is based on a particular class of dyadic-integer-coefficient based wavelet filters (DICWFs) which is formulated from the design of a half-band polynomial. To design integer-coefficient based half-band polynomial we used the splitting approach. Next, factorization is done for this designed half-band polynomial and assigned specific number of vanishing moments and ischolar_mains to achieve the dyadic-integer coefficients low-pass analysis and synthesis filters to reduce the hardware complexity. The discrete wavelet transform (DWT) obtained from DICWF is applied on the low-resolution image to obtain the high frequency sub-bands. These high frequency sub-bands and the original low-resolution image are then interpolated to enhance the resolution. Next, stationary wavelet transform (SWT) that are obtained using DICWFs is employed to minimize the loss due to the use of DWT. In addition, wavelet coefficients soft-thresholding scheme is used on these estimated high-frequency sub-bands in order to reduce the spatial domain noise. These sub-bands are combined together by inverse discrete wavelet transform obtained from DICWF to generate a high-resolution image. The proposed approach is validated based on quality metrics of existing filter banks and proposed filter banks.