Accurate and Fast Dense Stereo Matching Using Three-Mode Census to Compute Matching Costs and Adaptive Cross Windowing to Aggregate Costs

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Two common methods for cost aggregation in local stereo matching are the cross window and the weighted matching window methods. The adaptive weighted window method requires complex calculations to determine the weights, and therefore eliminates the main advantage of local methods, i.e. its high speed. The cross window method is faster than the adaptive weighted window because it is not necessary to define the weights from complex mathematical relationships, but its accuracy is less than the adaptive weighted window method. In the researches that use the cross-matching window, methods such as the absolute value of the color intensity difference or the normal Census transform are used to calculate the cost, the accuracy of which is not as good as the weighted matching window method. In this paper, the three-mode Census transform is used to calculate costs. This method is used along with two other methods, the absolute value of the color intensity difference and the absolute value of the gradient difference, together with the cross aggregation cost, leads to achieving good accuracy also the desired performance speed. Considering the experimental results on the Middlebury standard dataset confirms the desired performance of the proposed algoithm in terms of accuracy and execution speed.

Language:
Persian
Published:
Machine Vision and Image Processing, Volume:11 Issue: 2, 2024
Pages:
39 to 52
https://www.magiran.com/p2849270  
سامانه نویسندگان
  • Corresponding Author (2)
    Ali Mohammad Fotouhi
    Assistant Professor Electrical Engineering Department, Tafresh university, Tafarsh, Iran
    Fotouhi، Ali Mohammad
اطلاعات نویسنده(گان) توسط ایشان ثبت و تکمیل شده‌است. برای مشاهده مشخصات و فهرست همه مطالب، صفحه رزومه را ببینید.
مقالات دیگری از این نویسنده (گان)