Extension Program Delivery for Greenhouse Growers Using Compressed Video Technology

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 507d-507
Author(s):  
Steven E. Newman ◽  
Karen L. Panter
Keyword(s):  
Best Management Practices ◽  
Management Practices ◽  
Compressed Video ◽  
Educational Programming ◽  
Video Technology ◽  
Best Management ◽  
Personal Interaction ◽  
Session Evaluations ◽  
Greenhouse Growers ◽  
Extension Program

There is a need for educational programming for greenhouse growers on effective uses of biorational pesticides and biological controls of insect and mite pests, diseases, and alternatives to herbicide sprays in confined areas; however, in many states, travel for specialists for programming and workshops is becoming prohibitive. A series of programs outlining Best Management Practices (BMP) for the greenhouse industry outlining techniques and practices reducing pesticide use were conducted at multiple sites in Colorado simultaneously using interactive compressed video technology. This conferencing technology is gaining wide acceptance in many venues and provides an opportunity for wider participation of clientele without travel. Participants in the programs reported in post-session evaluations that they did miss the personal interaction with the speakers, but did acknowledge that not having to drive 5 hours to attend a seminar was quite beneficial.

A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

2021 ◽  
pp. 1-11
Author(s):  
Kusan Biswas
Keyword(s):  
Data Hiding ◽  
High Capacity ◽  
Error Correcting Codes ◽  
Human Vision ◽  
Data Embedding ◽  
Compressed Images ◽  
Matrix Encoding ◽  
Dct Coefficients ◽  
Capacity Data ◽  
Value Decomposition

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems  (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.

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