Effects of Transient and Nontransient Changes of Surface Feature on Object Correspondence

Object correspondence is a fundamental problem in perception. Classic theories hold that the computation of correspondence is solely based on spatiotemporal information. Recent research showed that surface features also play an important role. However, the surface features of objects in many studies did not change throughout a trial. This study investigated the effect of feature change on object correspondence using the object-reviewing paradigm. Two moving objects underwent transient feature changes on color dimension (Experiment 1A) or a combination of three dimensions (Experiment 2A). Moreover, the objects moved behind four occluders to make the feature change nontransient (Experiments 1B and 2B). Object-specific preview benefits were reduced or eliminated when feature changes were transient, but the benefits were not affected when feature changes were nontransient. The effects of transient versus nontransient changes of surface feature in object correspondence are discussed.

KLASIFIKASI OBJEK BERDASARKAN WARNA, BENTUK DAN DIMENSI

ABSTRACTThis research aimed to develop an algorithm to classify an object based on color, shape and dimension. In this research, the classification process was designed on two combined features which are color-shape, color-dimension, and shape-dimension. Each two combined features yielded 9 classification results. Therefore, in total, the number of classifications of three combined features were 27 classifications. The algorithm was depeloved as follows. The color feature was classiffied using RGB color histogram. Each object histogram was compared and calculated the distance to the reference object histogram. The similarity was determined with the smaller distance to the reference object. The shape feature was classified using shape matching algorihtm. The algorithm measured the similarity based on distance between two point on each geometry. The dimension feature was classified using the number of the pixel on each object. The number of pixel was callibrated on certain distance to the camera. The algoritma was also designed to classify the reject object (Not Good/NG). The algortihm was implemented on a conveyor system as a sorting machine. The conveyor has 10 output classification, 9 output for object classification and 1 output for NG object. The experimental results showed the sistem could classify the object in 27 category classification and 1 NG category.Keywords: object cleassification, object feature, RGB color histogram, shape matching, object sortingABSTRAKPenelitian ini bertujuan untuk membangun algoritma untuk pengklasifikasian objek berdasarkan warna, bentuk dan dimensi. Dalam penelitian ini, pengklasifikasian didesain dalam dua ciri gabungan yaitu warna-bentuk, warna-dimensi dan bentuk-dimensi. Tiap-tiap dua ciri gabungan tersebut akan menghasilkan 9 hasil klasifikasi. Sehingga total klasifikasi gabungan 3 ciri adalah 27 klasifikasi. Algoritma yang dikembangkan untuk masing-masing ciri adalah sebagai berikut. Ciri warna diklasifikasikan menggunakan histogram warna RGB. Tiap objek dibandingkan histogramnya dan dihitung jarak tiap histogram dengan histogram referensi. Semakin dekat dengan histogram referensi, maka objek tersebut diklasifikasikan sama dengan objek referensi. Ciri bentuk diklasifikasikan menggunakan algoritma shape matching. Algoritma shape matching mengukur kemiripan objek berdasarkan jarak antar titik dalam objek geometri. Semakin rendah perbedaannya menunjukkan semakin mirip objek tersebut. Sementara ciri dimensi diklasifikasikan menggunakan perhitungan jumlah pixel pada tiap objek. Jumlah pixel dikalibrasi pada jarak tertentu dari pengkapturan objek oleh kamera. Selain itu, algoritma ini pun didesain untuk dapat mengklasifikasi objek yang tidak masuk kategori dan diklasifikasikan sebagai objek yang rusak (Not Good/NG). Algoritma ini selanjutnya diimplemenasikan dalam sebuah konveyor sebagai mesih pemisah objek yang mempunyai 10 keluaran. Sembilan keluaran untuk objek hasil klasifikasi dan satu keluaran untuk objek dalam kategori NG. Hasil eksperimen menunjukkan sistem dapat mengklasifikasi objek dalam 27 kategori dan 1 kategori NG.Kata Kunci: klasifikasi objek, ciri objek, histogram warna RGB, shape mathing, pemilah objek

Dyeing of Poplar Wood through High-Pressure Processing: Performance Evaluation

Dyeing of poplar wood through high-pressure (HP) processing was evaluated at different pressure levels (40 to 130 MPa) and compared with conventional hot dip treatment. Dyeing performance was evaluated based on external surface color, fractal color dimension, dye uptake, internal color, elemental composition, and subsequent ultraviolet aging of the wood. The internal microstructure of the treated wood was also examined by scanning electron microscopy (SEM). Results showed that the external surface color difference and change in brightness were significantly greater with HP treatment than with hot dip treatment. The hue angle of HP treated wood surfaces was 1.27 to 4.01 higher and the fractal color dimension was significantly (p < 0.05) lower than that of hot dip treated wood, demonstrating more intense and more uniform distribution of color with HP treatment. The internal color of HP treated wood was also more evenly distributed and more intense, while the hot dip treated wood had no internal dye uptake (zero penetration). SEM analysis showed that the wood structure was damaged by HP treatment, which allowed the dye solution to penetrate into the wood more easily. Among the different pressure levels, the higher pressures resulted in better dyeing performance; however, considering the treatment cost, time, and energy efficiency, 100 MPa treatment may be more economical. Keywords: Color, Dyeing, Fractal dimension, High pressure, Hot dip, Poplar wood.

Mechanisms Underlying Transfer of Task-Defined Rules Across Feature Dimensions

The Simon effect can be reversed, favoring spatially noncorresponding responses, when people respond to stimulus colors (e.g., green) by pressing a key labeled with the alternative color (i.e., red). This Hedge and Marsh reversal is most often attributed to transfer of logical recoding rules from the color dimension to the location dimension. A recent study showed that this transfer of logical recoding rules can occur not only within a single task but also across two separate tasks that are intermixed. The present study investigated the conditions that determine the transfer of logical recoding rules across tasks. Experiment 1 examined whether it occurs in a transfer paradigm, that is when the two tasks are performed separately, but provided little support for this possibility. Experiment 2 investigated the role of task-set readiness, using a mixed-task paradigm with a predictable trials sequence, which indicated that there is no transfer of task-defined rules across tasks even when they are highly active during the Simon task. Finally, Experiments 3 and 4 used a mixed-task paradigm, where trials of the two tasks were mixed randomly and unpredictably, and manipulated the amount of feature overlap between tasks. Results indicated that task similarity is a determining factor for transfer of task-defined rules to occur. Overall, the study provides evidence that transfer of logical recoding rules tends to occur across two tasks when tasks are unpredictably intermixed and use stimuli that are highly similar and confusable.