Panu Srestasathiern

Learn More
This paper introduces a new representation for planar objects which is invariant to projective transformation. Proposed representation relies on a new shape basis which we refer to as the conic basis. The conic basis takes conic-section coefficients as its dimensions and represents the object as a convex combination of conic-sections. Pairs of(More)
In this paper, a software program is developed to monitor rice growing stages. Images are required as input data for the software. Using field server equipment, the images are obtained from two rice fields located in Suphanburi and Roi Et provinces, Thailand. Each daily image covers approximately 100 &#x00D7; 100 m<sup>2</sup> recorded by 720 &#x00D7; 480(More)
The paper presents an agricultural monitoring system developed for Thailand. Various species of plants have been directly observed from the agricultural fields which mainly consist of economic crops of Thailand such as rice, cassava, rubber, sugar cane, corn, etc. An equipment used to obtain the data is called field server, which has been installed at the(More)
This paper presents a novel method for extrinsic parameters estimation of a single line scan LiDAR and a camera. Using a checkerboard, the calibration setup is simple and practical. Particularly, the proposed calibration method is based on resolving geometry of the checkerboard that visible to the camera and the LiDAR. The calibration setup geometry is(More)
This paper introduces a method for the recognition planar objects under projective geometry. Our method is based on a similarity measure invariant to projec-tive transform. The proposed similarity measure utilizes the distribution of the projective relations between the conic section pairs, which are estimated from the ob-ject's shape. We conjecture that(More)
In this study, an algorithm is proposed to determine the duration in a rice crop cycle based on texture analysis. During an observation period in 2013, daily images were acquired from a still camera installed at a paddy field. Given a set of time-series images, the texture analysis is used to classify different stages of the rice growing. Regarding the(More)
In 2012, GISTDA has launched a sensor network project for monitoring agricultural fields in every region of Thailand. Integration of digital camera and weather sensors, Field Server (FS) is used to collect two types of data; image and weather condition. In this study, time-series images acquired from the rice field are used for computing and understanding(More)
Crop yield forecasting is important either for a government, agricultural industries or a trading company for their action plans. A very important variable to be given to a crop model used for the forecast is an accurate crop cultivation date. When the area of interest is large, it is preferable to use remote sensing data such as satellite images for the(More)